torsh-backend 0.1.2

//! Objectives and Constraints Module
//!
//! This module provides comprehensive objective function management and constraint handling
//! for CUDA memory optimization, including multi-objective optimization, Pareto front analysis,
//! and sophisticated constraint satisfaction systems.

use std::collections::HashMap;
use std::sync::{Arc, RwLock};
use std::time::{Duration, Instant};

// ============================================================================
// Stub implementations for missing types
// ============================================================================

#[derive(Debug, Clone, Default)]
pub struct AlgorithmPerformanceTracker {}
#[derive(Debug, Clone, Default)]
pub struct ConvergenceMonitor {}
#[derive(Debug, Clone, Default)]
pub struct DiversityMaintainer {}
#[derive(Debug, Clone, Default)]
pub struct InteractiveOptimizer {}
#[derive(Debug, Clone, Default)]
pub struct RobustMultiObjectiveOptimizer {}
#[derive(Debug, Clone, Default)]
pub struct DynamicMultiObjectiveHandler {}
#[derive(Debug, Clone, Default)]
pub struct PreferenceArticulationSystem {}
#[derive(Debug, Clone, Default)]
pub struct MultiObjectiveDecisionSupport {}
#[derive(Debug, Clone, Default)]
pub struct ConstraintSatisfactionEngine {}
#[derive(Debug, Clone, Default)]
pub struct ConstraintViolationDetector {}
#[derive(Debug, Clone, Default)]
pub struct PenaltyComputationSystem {}
#[derive(Debug, Clone, Default)]
pub struct ConstraintPropagationEngine {}
#[derive(Debug, Clone, Default)]
pub struct ConstraintConflictResolver {}
#[derive(Debug, Clone, Default)]
pub struct AdaptiveConstraintSystem {}
#[derive(Debug, Clone, Default)]
pub struct ConstraintLearningSystem {}
#[derive(Debug, Clone, Default)]
pub struct ConstraintUncertaintyHandler {}
#[derive(Debug, Clone, Default)]
pub struct ConstraintOptimizer {}
#[derive(Debug, Clone, Default)]
pub struct ConstraintMonitoringSystem {}
#[derive(Debug, Clone, Default)]
pub struct MathematicalExpression {}
#[derive(Debug, Clone, Default)]
pub struct InputVariable {}
#[derive(Debug, Clone, Default)]
pub struct ComputationalComplexity {}
#[derive(Debug, Clone, Default)]
pub struct EvaluationConfiguration {}
#[derive(Debug, Clone, Default)]
pub struct GradientInformation {}
#[derive(Debug, Clone, Default)]
pub struct HessianInformation {}
#[derive(Debug, Clone, Default)]
pub struct NoiseCharacteristics {}
#[derive(Debug, Clone, Default)]
pub struct MultiFidelityConfiguration {}
#[derive(Debug, Clone, Default)]
pub struct SurrogateIntegration {}
#[derive(Debug, Clone, Default)]
pub struct FunctionSensitivityAnalysis {}
#[derive(Debug, Clone, Default)]
pub struct FunctionValidationFramework {}
#[derive(Debug, Clone, Default)]
pub struct OptimizationResult {}

// ============================================================================

/// Comprehensive objective and constraint management system
#[derive(Debug)]
pub struct OptimizationObjectiveManager {
    /// Registry of optimization objectives
    objective_registry: ObjectiveRegistry,
    /// Constraint management system
    constraint_manager: ConstraintManager,
    /// Multi-objective optimization engine
    multi_objective_engine: MultiObjectiveEngine,
    /// Pareto front analyzer
    pareto_analyzer: ParetoFrontAnalyzer,
    /// Objective function evaluator
    function_evaluator: ObjectiveFunctionEvaluator,
    /// Constraint satisfaction checker
    satisfaction_checker: ConstraintSatisfactionChecker,
    /// Trade-off analysis system
    tradeoff_analyzer: TradeoffAnalyzer,
    /// Objective decomposition system
    decomposition_system: ObjectiveDecompositionSystem,
    /// Dynamic objective adjustment
    dynamic_adjustment: DynamicObjectiveAdjustment,
    /// Solution archive manager
    solution_archive: SolutionArchiveManager,
    /// Performance metrics tracker
    metrics_tracker: ObjectiveMetricsTracker,
    /// Visualization and reporting system
    visualization_system: ObjectiveVisualizationSystem,
}

/// Registry for managing optimization objectives
#[derive(Debug)]
pub struct ObjectiveRegistry {
    /// Registered objectives by ID
    objectives: Arc<RwLock<HashMap<String, OptimizationObjective>>>,
    /// Objectives by category
    categories: HashMap<ObjectiveCategory, Vec<String>>,
    /// Objective hierarchies
    hierarchies: HashMap<String, ObjectiveHierarchy>,
    /// Objective dependencies
    dependencies: DependencyGraph,
    /// Objective templates
    templates: HashMap<String, ObjectiveTemplate>,
    /// Custom objective factory
    objective_factory: ObjectiveFactory,
    /// Objective validation framework
    validation_framework: ObjectiveValidationFramework,
    /// Objective versioning system
    versioning_system: ObjectiveVersioningSystem,
}

/// Comprehensive optimization objective definition
#[derive(Debug, Clone)]
pub struct OptimizationObjective {
    /// Unique objective identifier
    pub id: String,
    /// Human-readable objective name
    pub name: String,
    /// Detailed objective description
    pub description: String,
    /// Objective type classification
    pub objective_type: ObjectiveType,
    /// Objective category
    pub category: ObjectiveCategory,
    /// Target value to achieve
    pub target_value: f64,
    /// Current measured value
    pub current_value: f64,
    /// Objective weight in multi-objective optimization
    pub weight: f32,
    /// Optimization direction
    pub direction: OptimizationDirection,
    /// Associated constraints
    pub constraints: Vec<ObjectiveConstraint>,
    /// Objective function definition
    pub function: ObjectiveFunction,
    /// Measurement configuration
    pub measurement_config: MeasurementConfiguration,
    /// Performance bounds
    pub bounds: ObjectiveBounds,
    /// Sensitivity analysis data
    pub sensitivity: SensitivityAnalysis,
    /// Historical performance data
    pub history: Vec<ObjectiveHistoryEntry>,
    /// Priority level
    pub priority: ObjectivePriority,
    /// Context dependencies
    pub context_dependencies: Vec<ContextDependency>,
    /// Quality assessment
    pub quality_assessment: ObjectiveQualityAssessment,
    /// Metadata and annotations
    pub metadata: ObjectiveMetadata,
    /// Validation rules
    pub validation_rules: Vec<ObjectiveValidationRule>,
    /// Success criteria
    pub success_criteria: Vec<SuccessCriterion>,
    /// Failure conditions
    pub failure_conditions: Vec<FailureCondition>,
}

/// Types of optimization objectives
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub enum ObjectiveType {
    /// Performance maximization objective
    Performance,
    /// Memory usage minimization
    MemoryUsage,
    /// Latency minimization
    Latency,
    /// Throughput maximization
    Throughput,
    /// Energy efficiency optimization
    Energy,
    /// Bandwidth utilization optimization
    Bandwidth,
    /// Cache hit rate maximization
    CacheHitRate,
    /// Error rate minimization
    ErrorRate,
    /// Resource utilization optimization
    ResourceUtilization,
    /// Cost minimization
    Cost,
    /// Quality of service optimization
    QualityOfService,
    /// Reliability maximization
    Reliability,
    /// Availability maximization
    Availability,
    /// Scalability optimization
    Scalability,
    /// Security score maximization
    Security,
    /// User experience optimization
    UserExperience,
    /// Environmental impact minimization
    EnvironmentalImpact,
    /// Maintainability optimization
    Maintainability,
    /// Fairness optimization
    Fairness,
    /// Robustness maximization
    Robustness,
    /// Custom objective type
    Custom(String),
}

/// Objective categories for organization
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub enum ObjectiveCategory {
    /// System performance objectives
    SystemPerformance,
    /// Resource efficiency objectives
    ResourceEfficiency,
    /// Quality objectives
    Quality,
    /// Business objectives
    Business,
    /// User experience objectives
    UserExperience,
    /// Operational objectives
    Operations,
    /// Security objectives
    Security,
    /// Compliance objectives
    Compliance,
    /// Research objectives
    Research,
    /// Custom category
    Custom(String),
}

/// Optimization direction specification
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum OptimizationDirection {
    /// Minimize the objective value
    Minimize,
    /// Maximize the objective value
    Maximize,
    /// Target a specific value
    Target(f64),
    /// Achieve value within a range
    Range { min: f64, max: f64 },
    /// Maintain stability around current value
    Stabilize { tolerance: f64 },
    /// Follow a trajectory over time
    Trajectory { path: TrajectoryPath },
    /// Satisfy multiple conditions
    MultiCondition {
        conditions: Vec<OptimizationCondition>,
    },
}

/// Objective constraint definition
#[derive(Debug, Clone)]
pub struct ObjectiveConstraint {
    /// Constraint identifier
    pub id: String,
    /// Constraint name
    pub name: String,
    /// Constraint description
    pub description: String,
    /// Constraint type
    pub constraint_type: ConstraintType,
    /// Constraint value or bound
    pub value: ConstraintValue,
    /// Constraint priority
    pub priority: ConstraintPriority,
    /// Constraint strictness
    pub strictness: ConstraintStrictness,
    /// Violation penalty function
    pub penalty_function: PenaltyFunction,
    /// Constraint satisfaction tolerance
    pub tolerance: f64,
    /// Context-dependent activation
    pub activation_conditions: Vec<ActivationCondition>,
    /// Constraint dependencies
    pub dependencies: Vec<ConstraintDependency>,
    /// Temporal properties
    pub temporal_properties: TemporalConstraintProperties,
    /// Validation configuration
    pub validation_config: ConstraintValidationConfig,
    /// Historical violation data
    pub violation_history: Vec<ConstraintViolation>,
    /// Adaptation rules
    pub adaptation_rules: Vec<ConstraintAdaptationRule>,
}

/// Types of constraints in optimization
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub enum ConstraintType {
    /// Hard constraint that must be satisfied
    Hard,
    /// Soft constraint with penalty for violation
    Soft,
    /// Elastic constraint that can adapt
    Elastic,
    /// Preference constraint
    Preference,
    /// Resource constraint
    Resource,
    /// Performance constraint
    Performance,
    /// Safety constraint
    Safety,
    /// Legal/regulatory constraint
    Regulatory,
    /// Business rule constraint
    BusinessRule,
    /// Technical limitation constraint
    Technical,
    /// Environmental constraint
    Environmental,
    /// Quality constraint
    Quality,
    /// Security constraint
    Security,
    /// Temporal constraint
    Temporal,
    /// Stochastic constraint
    Stochastic,
    /// Robust constraint
    Robust,
    /// Chance constraint
    Chance,
    /// Custom constraint type
    Custom(String),
}

/// Constraint priority levels
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub enum ConstraintPriority {
    /// Lowest priority
    VeryLow,
    /// Low priority
    Low,
    /// Medium priority
    Medium,
    /// High priority
    High,
    /// Very high priority
    VeryHigh,
    /// Critical priority
    Critical,
    /// Emergency priority
    Emergency,
}

/// Multi-objective optimization engine
#[derive(Debug)]
pub struct MultiObjectiveEngine {
    /// Available optimization algorithms
    algorithms: HashMap<String, Box<dyn MultiObjectiveAlgorithm>>,
    /// Current Pareto front solutions
    pareto_front: ParetoFront,
    /// Solution archive
    solution_archive: SolutionArchive,
    /// Algorithm performance tracker
    algorithm_tracker: AlgorithmPerformanceTracker,
    /// Convergence monitor
    convergence_monitor: ConvergenceMonitor,
    /// Solution diversity maintainer
    diversity_maintainer: DiversityMaintainer,
    /// Interactive optimization support
    interactive_optimizer: InteractiveOptimizer,
    /// Robust optimization framework
    robust_optimizer: RobustMultiObjectiveOptimizer,
    /// Dynamic multi-objective handling
    dynamic_handler: DynamicMultiObjectiveHandler,
    /// Preference articulation system
    preference_system: PreferenceArticulationSystem,
    /// Decision making support
    decision_support: MultiObjectiveDecisionSupport,
}

/// Pareto front representation and analysis
#[derive(Debug, Clone)]
pub struct ParetoFront {
    /// Solutions on the Pareto front
    pub solutions: Vec<ParetoSolution>,
    /// Front generation metadata
    pub generation: u32,
    /// Quality metrics
    pub quality_metrics: ParetoQualityMetrics,
    /// Dominance relationships
    pub dominance_matrix: DominanceMatrix,
    /// Reference points
    pub reference_points: Vec<ReferencePoint>,
    /// Ideal and nadir points
    pub ideal_point: Vec<f64>,
    pub nadir_point: Vec<f64>,
    /// Front approximation quality
    pub approximation_quality: ApproximationQuality,
    /// Stability measures
    pub stability_measures: FrontStabilityMeasures,
    /// Visualization data
    pub visualization_data: FrontVisualizationData,
    /// Statistical analysis
    pub statistical_analysis: FrontStatisticalAnalysis,
}

/// Individual Pareto optimal solution
#[derive(Debug, Clone)]
pub struct ParetoSolution {
    /// Unique solution identifier
    pub id: String,
    /// Solution parameters
    pub parameters: HashMap<String, f64>,
    /// Objective values achieved
    pub objectives: HashMap<String, f64>,
    /// Constraint satisfaction status
    pub constraint_satisfaction: Vec<ConstraintSatisfactionStatus>,
    /// Solution quality score
    pub quality_score: f32,
    /// Dominance rank
    pub dominance_rank: u32,
    /// Crowding distance
    pub crowding_distance: f64,
    /// Solution age (generations since creation)
    pub age: u32,
    /// Solution stability measure
    pub stability: f32,
    /// Resource requirements
    pub resource_requirements: ResourceRequirements,
    /// Implementation complexity
    pub implementation_complexity: f32,
    /// Risk assessment
    pub risk_assessment: SolutionRiskAssessment,
    /// Performance prediction confidence
    pub prediction_confidence: f32,
    /// Solution metadata
    pub metadata: SolutionMetadata,
    /// Validation results
    pub validation_results: SolutionValidationResults,
    /// User feedback
    pub user_feedback: Option<UserFeedback>,
}

/// Constraint management system
#[derive(Debug)]
pub struct ConstraintManager {
    /// Active constraints registry
    constraints: HashMap<String, ObjectiveConstraint>,
    /// Constraint satisfaction engine
    satisfaction_engine: ConstraintSatisfactionEngine,
    /// Constraint violation detector
    violation_detector: ConstraintViolationDetector,
    /// Penalty computation system
    penalty_system: PenaltyComputationSystem,
    /// Constraint propagation engine
    propagation_engine: ConstraintPropagationEngine,
    /// Conflict resolution system
    conflict_resolver: ConstraintConflictResolver,
    /// Dynamic constraint adaptation
    adaptive_system: AdaptiveConstraintSystem,
    /// Constraint learning system
    learning_system: ConstraintLearningSystem,
    /// Uncertainty handling
    uncertainty_handler: ConstraintUncertaintyHandler,
    /// Constraint optimization
    constraint_optimizer: ConstraintOptimizer,
    /// Monitoring and alerting
    monitoring_system: ConstraintMonitoringSystem,
}

/// Objective function definition and evaluation
#[derive(Debug, Clone)]
pub struct ObjectiveFunction {
    /// Function identifier
    pub id: String,
    /// Function name
    pub name: String,
    /// Function type
    pub function_type: ObjectiveFunctionType,
    /// Mathematical expression
    pub expression: MathematicalExpression,
    /// Input variables
    pub input_variables: Vec<InputVariable>,
    /// Function parameters
    pub parameters: HashMap<String, f64>,
    /// Computational complexity
    pub complexity: ComputationalComplexity,
    /// Evaluation configuration
    pub evaluation_config: EvaluationConfiguration,
    /// Gradient information
    pub gradient_info: GradientInformation,
    /// Hessian information
    pub hessian_info: HessianInformation,
    /// Noise characteristics
    pub noise_characteristics: NoiseCharacteristics,
    /// Multi-fidelity configuration
    pub multi_fidelity: MultiFidelityConfiguration,
    /// Surrogate model integration
    pub surrogate_integration: SurrogateIntegration,
    /// Sensitivity analysis
    pub sensitivity_analysis: FunctionSensitivityAnalysis,
    /// Validation framework
    pub validation: FunctionValidationFramework,
}

/// Types of objective functions
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum ObjectiveFunctionType {
    /// Linear function
    Linear,
    /// Quadratic function
    Quadratic,
    /// Polynomial function
    Polynomial,
    /// Exponential function
    Exponential,
    /// Logarithmic function
    Logarithmic,
    /// Trigonometric function
    Trigonometric,
    /// Composite function
    Composite,
    /// Black-box function
    BlackBox,
    /// Machine learning model
    MLModel,
    /// Simulation-based function
    Simulation,
    /// Empirical function
    Empirical,
    /// Stochastic function
    Stochastic,
    /// Multi-modal function
    MultiModal,
    /// Discontinuous function
    Discontinuous,
    /// Custom function type
    Custom(String),
}

impl OptimizationObjectiveManager {
    /// Create a new objective manager
    pub fn new(config: ObjectiveManagerConfig) -> Self {
        Self {
            objective_registry: ObjectiveRegistry::new(config.registry_config.clone()),
            constraint_manager: ConstraintManager::new(config.constraint_config.clone()),
            multi_objective_engine: MultiObjectiveEngine::new(
                config.multi_objective_config.clone(),
            ),
            pareto_analyzer: ParetoFrontAnalyzer::new(config.pareto_config.clone()),
            function_evaluator: ObjectiveFunctionEvaluator::new(config.evaluator_config.clone()),
            satisfaction_checker: ConstraintSatisfactionChecker::new(
                config.satisfaction_config.clone(),
            ),
            tradeoff_analyzer: TradeoffAnalyzer::new(config.tradeoff_config.clone()),
            decomposition_system: ObjectiveDecompositionSystem::new(
                config.decomposition_config.clone(),
            ),
            dynamic_adjustment: DynamicObjectiveAdjustment::new(config.dynamic_config.clone()),
            solution_archive: SolutionArchiveManager::new(config.archive_config.clone()),
            metrics_tracker: ObjectiveMetricsTracker::new(config.metrics_config.clone()),
            visualization_system: ObjectiveVisualizationSystem::new(
                config.visualization_config.clone(),
            ),
        }
    }

    /// Register a new optimization objective
    pub fn register_objective(
        &mut self,
        objective: OptimizationObjective,
    ) -> Result<(), ObjectiveError> {
        // Validate objective
        self.validate_objective(&objective)?;

        // Register in registry
        self.objective_registry.register(objective.clone())?;

        // Initialize tracking
        self.metrics_tracker
            .initialize_objective_tracking(&objective.id)?;

        // Update dependency graph
        self.update_objective_dependencies(&objective)?;

        Ok(())
    }

    /// Register a constraint
    pub fn register_constraint(
        &mut self,
        constraint: ObjectiveConstraint,
    ) -> Result<(), ObjectiveError> {
        // Validate constraint
        self.validate_constraint(&constraint)?;

        // Register in constraint manager
        self.constraint_manager.register_constraint(constraint)?;

        Ok(())
    }

    /// Evaluate objectives for given solution
    pub fn evaluate_objectives(
        &mut self,
        solution_parameters: &HashMap<String, f64>,
        context: &EvaluationContext,
    ) -> Result<ObjectiveEvaluationResult, ObjectiveError> {
        let mut evaluation_results = HashMap::new();

        // Get active objectives
        let active_objectives = self.objective_registry.get_active_objectives(context)?;

        // Evaluate each objective
        for objective in &active_objectives {
            let objective_value = self.function_evaluator.evaluate_objective(
                objective,
                solution_parameters,
                context,
            )?;
            evaluation_results.insert(objective.id.clone(), objective_value);
        }

        // Check constraint satisfaction
        let constraint_results = self
            .constraint_manager
            .check_constraints(solution_parameters, context)?;

        // Calculate aggregate metrics
        let aggregate_metrics =
            self.calculate_aggregate_metrics(&evaluation_results, &constraint_results)?;

        // Record evaluation
        self.metrics_tracker
            .record_evaluation(&evaluation_results, &constraint_results)?;

        Ok(ObjectiveEvaluationResult {
            objective_values: evaluation_results,
            constraint_results,
            aggregate_metrics,
            evaluation_metadata: self.create_evaluation_metadata(context)?,
            quality_assessment: self
                .assess_evaluation_quality(&evaluation_results, &constraint_results)?,
            timestamp: Instant::now(),
        })
    }

    /// Perform multi-objective optimization
    pub fn optimize_multi_objective(
        &mut self,
        optimization_config: MultiObjectiveConfig,
    ) -> Result<MultiObjectiveResult, ObjectiveError> {
        // Initialize optimization
        let mut optimization_session = self
            .multi_objective_engine
            .create_session(optimization_config.clone())?;

        // Run optimization algorithm
        let optimization_result = self
            .multi_objective_engine
            .optimize(&mut optimization_session)?;

        // Analyze Pareto front
        let pareto_analysis = self
            .pareto_analyzer
            .analyze_front(&optimization_result.pareto_front)?;

        // Generate recommendations
        let recommendations =
            self.generate_multi_objective_recommendations(&optimization_result, &pareto_analysis)?;

        // Update solution archive
        self.solution_archive
            .add_solutions(&optimization_result.pareto_front.solutions)?;

        Ok(MultiObjectiveResult {
            pareto_front: optimization_result.pareto_front,
            convergence_metrics: optimization_result.convergence_metrics,
            algorithm_performance: optimization_result.algorithm_performance,
            pareto_analysis,
            recommendations,
            optimization_duration: optimization_result.duration,
            resource_usage: optimization_result.resource_usage,
        })
    }

    /// Analyze trade-offs between objectives
    pub fn analyze_tradeoffs(
        &self,
        objectives: &[String],
        context: &TradeoffContext,
    ) -> Result<TradeoffAnalysis, ObjectiveError> {
        self.tradeoff_analyzer.analyze_tradeoffs(
            objectives,
            context,
            &self.objective_registry,
            &self.solution_archive,
        )
    }

    /// Get Pareto front solutions
    pub fn get_pareto_front(&self) -> Result<ParetoFront, ObjectiveError> {
        self.multi_objective_engine.get_current_pareto_front()
    }

    /// Decompose complex objective into simpler sub-objectives
    pub fn decompose_objective(
        &mut self,
        objective_id: &str,
        decomposition_config: DecompositionConfig,
    ) -> Result<Vec<OptimizationObjective>, ObjectiveError> {
        let objective = self.objective_registry.get_objective(objective_id)?;
        self.decomposition_system
            .decompose_objective(&objective, decomposition_config)
    }

    /// Dynamically adjust objective weights
    pub fn adjust_objective_weights(
        &mut self,
        adjustments: HashMap<String, f32>,
        context: &AdjustmentContext,
    ) -> Result<(), ObjectiveError> {
        // Validate adjustments
        self.validate_weight_adjustments(&adjustments)?;

        // Apply adjustments
        self.dynamic_adjustment
            .adjust_weights(adjustments, context)?;

        // Update multi-objective engine
        self.multi_objective_engine
            .update_weights(&self.dynamic_adjustment.get_current_weights())?;

        Ok(())
    }

    /// Find compromise solutions
    pub fn find_compromise_solutions(
        &self,
        preferences: &UserPreferences,
    ) -> Result<Vec<ParetoSolution>, ObjectiveError> {
        let current_front = self.get_pareto_front()?;
        self.pareto_analyzer
            .find_compromise_solutions(&current_front, preferences)
    }

    /// Interactive optimization session
    pub fn start_interactive_optimization(
        &mut self,
        config: InteractiveOptimizationConfig,
    ) -> Result<InteractiveSession, ObjectiveError> {
        self.multi_objective_engine
            .start_interactive_session(config)
    }

    /// Validate objective consistency
    pub fn validate_objective_consistency(&self) -> Result<ConsistencyReport, ObjectiveError> {
        let objectives = self.objective_registry.get_all_objectives();
        let constraints = self.constraint_manager.get_all_constraints();

        let mut consistency_report = ConsistencyReport::new();

        // Check for conflicting objectives
        let conflicts = self.detect_objective_conflicts(&objectives)?;
        consistency_report.objective_conflicts = conflicts;

        // Check for infeasible constraints
        let infeasible_constraints = self
            .constraint_manager
            .detect_infeasible_constraints(&constraints)?;
        consistency_report.infeasible_constraints = infeasible_constraints;

        // Check for redundant constraints
        let redundant_constraints = self
            .constraint_manager
            .detect_redundant_constraints(&constraints)?;
        consistency_report.redundant_constraints = redundant_constraints;

        // Validate objective-constraint compatibility
        let compatibility_issues =
            self.validate_objective_constraint_compatibility(&objectives, &constraints)?;
        consistency_report.compatibility_issues = compatibility_issues;

        Ok(consistency_report)
    }

    /// Export objectives and constraints configuration
    pub fn export_configuration(&self) -> Result<ObjectiveConfigurationExport, ObjectiveError> {
        let objectives = self.objective_registry.export_objectives()?;
        let constraints = self.constraint_manager.export_constraints()?;
        let pareto_archive = self.solution_archive.export_solutions()?;

        Ok(ObjectiveConfigurationExport {
            objectives,
            constraints,
            pareto_archive,
            metadata: self.create_export_metadata(),
            version: "1.0".to_string(),
            timestamp: Instant::now(),
        })
    }

    /// Import objectives and constraints configuration
    pub fn import_configuration(
        &mut self,
        config: ObjectiveConfigurationImport,
    ) -> Result<ImportReport, ObjectiveError> {
        let mut import_report = ImportReport::new();

        // Import objectives
        for objective in config.objectives {
            match self.register_objective(objective.clone()) {
                Ok(()) => import_report.successful_objectives.push(objective.id),
                Err(e) => import_report.failed_objectives.push((objective.id, e)),
            }
        }

        // Import constraints
        for constraint in config.constraints {
            match self.register_constraint(constraint.clone()) {
                Ok(()) => import_report.successful_constraints.push(constraint.id),
                Err(e) => import_report.failed_constraints.push((constraint.id, e)),
            }
        }

        // Import solutions
        if let Some(solutions) = config.pareto_archive {
            self.solution_archive.import_solutions(solutions)?;
        }

        Ok(import_report)
    }

    /// Get objective analytics dashboard
    pub fn get_analytics_dashboard(&self) -> Result<ObjectiveAnalyticsDashboard, ObjectiveError> {
        let objective_metrics = self.metrics_tracker.get_comprehensive_metrics();
        let pareto_metrics = self.pareto_analyzer.get_front_metrics();
        let constraint_metrics = self.constraint_manager.get_satisfaction_metrics();
        let tradeoff_insights = self.tradeoff_analyzer.get_insights();

        Ok(ObjectiveAnalyticsDashboard {
            objective_metrics,
            pareto_metrics,
            constraint_metrics,
            tradeoff_insights,
            solution_statistics: self.solution_archive.get_statistics(),
            performance_trends: self.metrics_tracker.get_performance_trends(),
            recommendation_insights: self.generate_dashboard_recommendations()?,
        })
    }

    // Private helper methods

    fn validate_objective(&self, objective: &OptimizationObjective) -> Result<(), ObjectiveError> {
        // Validate objective structure
        if objective.id.is_empty() {
            return Err(ObjectiveError::InvalidObjective(
                "Objective ID cannot be empty".to_string(),
            ));
        }

        // Validate objective function
        self.function_evaluator
            .validate_function(&objective.function)?;

        // Validate constraints
        for constraint in &objective.constraints {
            self.validate_constraint(constraint)?;
        }

        Ok(())
    }

    fn validate_constraint(&self, constraint: &ObjectiveConstraint) -> Result<(), ObjectiveError> {
        // Validate constraint structure
        if constraint.id.is_empty() {
            return Err(ObjectiveError::InvalidConstraint(
                "Constraint ID cannot be empty".to_string(),
            ));
        }

        // Validate constraint value
        match &constraint.value {
            ConstraintValue::Single(v) => {
                if !v.is_finite() {
                    return Err(ObjectiveError::InvalidConstraint(
                        "Constraint value must be finite".to_string(),
                    ));
                }
            }
            ConstraintValue::Range { min, max } => {
                if !min.is_finite() || !max.is_finite() || min > max {
                    return Err(ObjectiveError::InvalidConstraint(
                        "Invalid constraint range".to_string(),
                    ));
                }
            }
            _ => {} // Other validation as needed
        }

        Ok(())
    }

    fn update_objective_dependencies(
        &mut self,
        objective: &OptimizationObjective,
    ) -> Result<(), ObjectiveError> {
        // Update dependency graph based on objective dependencies
        for dependency in &objective.context_dependencies {
            self.objective_registry
                .add_dependency(&objective.id, &dependency.dependency_id)?;
        }
        Ok(())
    }

    fn calculate_aggregate_metrics(
        &self,
        objective_results: &HashMap<String, f64>,
        constraint_results: &ConstraintSatisfactionResult,
    ) -> Result<AggregateMetrics, ObjectiveError> {
        let mut aggregate = AggregateMetrics::new();

        // Calculate weighted objective score
        let mut weighted_sum = 0.0;
        let mut total_weight = 0.0;

        for (objective_id, value) in objective_results {
            if let Ok(objective) = self.objective_registry.get_objective(objective_id) {
                weighted_sum += value * objective.weight as f64;
                total_weight += objective.weight as f64;
            }
        }

        if total_weight > 0.0 {
            aggregate.weighted_objective_score = weighted_sum / total_weight;
        }

        // Calculate constraint violation penalty
        aggregate.constraint_violation_penalty = constraint_results.total_penalty;

        // Calculate overall fitness
        aggregate.overall_fitness =
            aggregate.weighted_objective_score - aggregate.constraint_violation_penalty;

        Ok(aggregate)
    }

    fn create_evaluation_metadata(
        &self,
        context: &EvaluationContext,
    ) -> Result<EvaluationMetadata, ObjectiveError> {
        Ok(EvaluationMetadata {
            context: context.clone(),
            timestamp: Instant::now(),
            evaluator_version: "1.0".to_string(),
            computational_resources: self.measure_computational_resources(),
        })
    }

    fn assess_evaluation_quality(
        &self,
        objective_results: &HashMap<String, f64>,
        constraint_results: &ConstraintSatisfactionResult,
    ) -> Result<EvaluationQualityAssessment, ObjectiveError> {
        let mut quality = EvaluationQualityAssessment::new();

        // Assess objective value quality
        quality.objective_quality = self.assess_objective_quality(objective_results)?;

        // Assess constraint satisfaction quality
        quality.constraint_quality = constraint_results.satisfaction_rate;

        // Calculate overall quality
        quality.overall_quality = (quality.objective_quality + quality.constraint_quality) / 2.0;

        Ok(quality)
    }

    fn assess_objective_quality(
        &self,
        results: &HashMap<String, f64>,
    ) -> Result<f32, ObjectiveError> {
        // Calculate objective quality based on achieved values vs targets
        let mut quality_sum = 0.0;
        let mut count = 0;

        for (objective_id, value) in results {
            if let Ok(objective) = self.objective_registry.get_objective(objective_id) {
                let target_achievement = self.calculate_target_achievement(&objective, *value);
                quality_sum += target_achievement;
                count += 1;
            }
        }

        Ok(if count > 0 {
            quality_sum / count as f32
        } else {
            0.0
        })
    }

    fn calculate_target_achievement(
        &self,
        objective: &OptimizationObjective,
        achieved_value: f64,
    ) -> f32 {
        match objective.direction {
            OptimizationDirection::Minimize => {
                if achieved_value <= objective.target_value {
                    1.0
                } else {
                    (objective.target_value / achieved_value).max(0.0) as f32
                }
            }
            OptimizationDirection::Maximize => {
                if achieved_value >= objective.target_value {
                    1.0
                } else {
                    (achieved_value / objective.target_value).max(0.0) as f32
                }
            }
            OptimizationDirection::Target(target) => {
                let deviation = (achieved_value - target).abs();
                let tolerance = target * 0.1; // 10% tolerance
                (1.0 - (deviation / tolerance).min(1.0)) as f32
            }
            _ => 0.5, // Default for complex directions
        }
    }

    fn generate_multi_objective_recommendations(
        &self,
        result: &MultiObjectiveOptimizationResult,
        analysis: &ParetoAnalysis,
    ) -> Result<Vec<MultiObjectiveRecommendation>, ObjectiveError> {
        let mut recommendations = Vec::new();

        // Recommend best compromise solutions
        if !result.pareto_front.solutions.is_empty() {
            let knee_solutions = analysis.find_knee_solutions(&result.pareto_front)?;
            for solution in knee_solutions {
                recommendations.push(MultiObjectiveRecommendation {
                    recommendation_type: RecommendationType::KneeSolution,
                    solution_id: solution.id,
                    rationale: "This solution represents a good compromise between all objectives"
                        .to_string(),
                    confidence: 0.8,
                    expected_benefits: self.calculate_expected_benefits(&solution)?,
                });
            }
        }

        // Recommend objectives to focus on
        let objective_importance = analysis.analyze_objective_importance()?;
        for (objective_id, importance) in objective_importance.iter().take(3) {
            recommendations.push(MultiObjectiveRecommendation {
                recommendation_type: RecommendationType::FocusObjective,
                solution_id: String::new(),
                rationale: format!(
                    "Focusing on {} could yield significant improvements",
                    objective_id
                ),
                confidence: importance * 0.9,
                expected_benefits: HashMap::new(),
            });
        }

        Ok(recommendations)
    }

    fn calculate_expected_benefits(
        &self,
        solution: &ParetoSolution,
    ) -> Result<HashMap<String, f64>, ObjectiveError> {
        // Calculate expected benefits from implementing this solution
        let mut benefits = HashMap::new();

        for (objective_id, value) in &solution.objectives {
            if let Ok(objective) = self.objective_registry.get_objective(objective_id) {
                let improvement = self.calculate_improvement(&objective, *value);
                benefits.insert(objective_id.clone(), improvement);
            }
        }

        Ok(benefits)
    }

    fn calculate_improvement(&self, objective: &OptimizationObjective, achieved_value: f64) -> f64 {
        match objective.direction {
            OptimizationDirection::Minimize => {
                if objective.current_value > achieved_value {
                    (objective.current_value - achieved_value) / objective.current_value
                } else {
                    0.0
                }
            }
            OptimizationDirection::Maximize => {
                if achieved_value > objective.current_value {
                    (achieved_value - objective.current_value) / objective.current_value
                } else {
                    0.0
                }
            }
            OptimizationDirection::Target(target) => {
                let current_deviation = (objective.current_value - target).abs();
                let new_deviation = (achieved_value - target).abs();
                if new_deviation < current_deviation {
                    (current_deviation - new_deviation) / current_deviation
                } else {
                    0.0
                }
            }
            _ => 0.0,
        }
    }

    fn validate_weight_adjustments(
        &self,
        adjustments: &HashMap<String, f32>,
    ) -> Result<(), ObjectiveError> {
        for (objective_id, weight) in adjustments {
            // Check if objective exists
            self.objective_registry.get_objective(objective_id)?;

            // Check if weight is valid
            if !weight.is_finite() || *weight < 0.0 {
                return Err(ObjectiveError::InvalidWeight(format!(
                    "Invalid weight {} for objective {}",
                    weight, objective_id
                )));
            }
        }
        Ok(())
    }

    fn detect_objective_conflicts(
        &self,
        objectives: &[OptimizationObjective],
    ) -> Result<Vec<ObjectiveConflict>, ObjectiveError> {
        let mut conflicts = Vec::new();

        // Check for directly conflicting objectives
        for i in 0..objectives.len() {
            for j in (i + 1)..objectives.len() {
                if self.are_objectives_conflicting(&objectives[i], &objectives[j])? {
                    conflicts.push(ObjectiveConflict {
                        objective1: objectives[i].id.clone(),
                        objective2: objectives[j].id.clone(),
                        conflict_type: ConflictType::DirectConflict,
                        severity: self.assess_conflict_severity(&objectives[i], &objectives[j]),
                        resolution_suggestions: self.generate_conflict_resolution_suggestions(
                            &objectives[i],
                            &objectives[j],
                        )?,
                    });
                }
            }
        }

        Ok(conflicts)
    }

    fn are_objectives_conflicting(
        &self,
        obj1: &OptimizationObjective,
        obj2: &OptimizationObjective,
    ) -> Result<bool, ObjectiveError> {
        // Simplified conflict detection - in practice this would be more sophisticated
        match (obj1.objective_type, obj2.objective_type) {
            (ObjectiveType::Performance, ObjectiveType::MemoryUsage) => Ok(true),
            (ObjectiveType::Throughput, ObjectiveType::Latency) => Ok(true),
            (ObjectiveType::Performance, ObjectiveType::Energy) => Ok(true),
            _ => Ok(false),
        }
    }

    fn assess_conflict_severity(
        &self,
        obj1: &OptimizationObjective,
        obj2: &OptimizationObjective,
    ) -> ConflictSeverity {
        // Assess conflict severity based on weights and importance
        let combined_weight = obj1.weight + obj2.weight;
        if combined_weight > 1.5 {
            ConflictSeverity::High
        } else if combined_weight > 1.0 {
            ConflictSeverity::Medium
        } else {
            ConflictSeverity::Low
        }
    }

    fn generate_conflict_resolution_suggestions(
        &self,
        obj1: &OptimizationObjective,
        obj2: &OptimizationObjective,
    ) -> Result<Vec<ResolutionSuggestion>, ObjectiveError> {
        let mut suggestions = Vec::new();

        suggestions.push(ResolutionSuggestion {
            suggestion_type: SuggestionType::WeightAdjustment,
            description: "Adjust objective weights to balance trade-offs".to_string(),
            implementation_effort: ImplementationEffort::Low,
            expected_effectiveness: 0.7,
        });

        suggestions.push(ResolutionSuggestion {
            suggestion_type: SuggestionType::ObjectiveReformulation,
            description: "Consider reformulating objectives to reduce conflict".to_string(),
            implementation_effort: ImplementationEffort::Medium,
            expected_effectiveness: 0.8,
        });

        Ok(suggestions)
    }

    fn validate_objective_constraint_compatibility(
        &self,
        objectives: &[OptimizationObjective],
        constraints: &[ObjectiveConstraint],
    ) -> Result<Vec<CompatibilityIssue>, ObjectiveError> {
        let mut issues = Vec::new();

        for objective in objectives {
            for constraint in constraints {
                if let Some(issue) =
                    self.check_objective_constraint_compatibility(objective, constraint)?
                {
                    issues.push(issue);
                }
            }
        }

        Ok(issues)
    }

    fn check_objective_constraint_compatibility(
        &self,
        objective: &OptimizationObjective,
        constraint: &ObjectiveConstraint,
    ) -> Result<Option<CompatibilityIssue>, ObjectiveError> {
        // Check if objective and constraint are compatible
        // This is a simplified implementation
        Ok(None)
    }

    fn create_export_metadata(&self) -> ExportMetadata {
        ExportMetadata {
            exporter_version: "1.0".to_string(),
            export_timestamp: Instant::now(),
            total_objectives: self.objective_registry.count_objectives(),
            total_constraints: self.constraint_manager.count_constraints(),
            pareto_solutions_count: self.solution_archive.count_solutions(),
        }
    }

    fn measure_computational_resources(&self) -> ComputationalResources {
        // Measure current computational resource usage
        ComputationalResources {
            cpu_usage: 0.5,
            memory_usage: 1024 * 1024 * 100, // 100 MB
            execution_time: Duration::from_millis(100),
        }
    }

    fn generate_dashboard_recommendations(
        &self,
    ) -> Result<Vec<DashboardRecommendation>, ObjectiveError> {
        // Generate recommendations for the analytics dashboard
        Ok(Vec::new())
    }
}

// Implementation for ObjectiveRegistry
impl ObjectiveRegistry {
    /// Create a new objective registry
    pub fn new(config: ObjectiveRegistryConfig) -> Self {
        Self {
            objectives: Arc::new(RwLock::new(HashMap::new())),
            categories: HashMap::new(),
            hierarchies: HashMap::new(),
            dependencies: DependencyGraph::new(),
            templates: HashMap::new(),
            objective_factory: ObjectiveFactory::new(),
            validation_framework: ObjectiveValidationFramework::new(),
            versioning_system: ObjectiveVersioningSystem::new(),
        }
    }

    /// Register an objective
    pub fn register(&mut self, objective: OptimizationObjective) -> Result<(), ObjectiveError> {
        let mut objectives = self
            .objectives
            .write()
            .map_err(|_| ObjectiveError::LockError)?;

        if objectives.contains_key(&objective.id) {
            return Err(ObjectiveError::ObjectiveAlreadyExists(objective.id));
        }

        // Update categories
        self.categories
            .entry(objective.category)
            .or_insert_with(Vec::new)
            .push(objective.id.clone());

        // Store objective
        objectives.insert(objective.id.clone(), objective);

        Ok(())
    }

    /// Get an objective by ID
    pub fn get_objective(
        &self,
        objective_id: &str,
    ) -> Result<OptimizationObjective, ObjectiveError> {
        let objectives = self
            .objectives
            .read()
            .map_err(|_| ObjectiveError::LockError)?;
        objectives
            .get(objective_id)
            .cloned()
            .ok_or_else(|| ObjectiveError::ObjectiveNotFound(objective_id.to_string()))
    }

    /// Get active objectives for context
    pub fn get_active_objectives(
        &self,
        context: &EvaluationContext,
    ) -> Result<Vec<OptimizationObjective>, ObjectiveError> {
        let objectives = self
            .objectives
            .read()
            .map_err(|_| ObjectiveError::LockError)?;

        let active: Vec<_> = objectives
            .values()
            .filter(|obj| self.is_objective_active(obj, context))
            .cloned()
            .collect();

        Ok(active)
    }

    /// Get all objectives
    pub fn get_all_objectives(&self) -> Vec<OptimizationObjective> {
        let objectives = self.objectives.read().expect("lock should not be poisoned");
        objectives.values().cloned().collect()
    }

    /// Export objectives
    pub fn export_objectives(&self) -> Result<Vec<OptimizationObjective>, ObjectiveError> {
        Ok(self.get_all_objectives())
    }

    /// Add dependency between objectives
    pub fn add_dependency(
        &mut self,
        objective_id: &str,
        dependency_id: &str,
    ) -> Result<(), ObjectiveError> {
        self.dependencies
            .add_dependency(objective_id, dependency_id)
    }

    /// Count objectives
    pub fn count_objectives(&self) -> usize {
        let objectives = self.objectives.read().expect("lock should not be poisoned");
        objectives.len()
    }

    // Private helper methods

    fn is_objective_active(
        &self,
        objective: &OptimizationObjective,
        context: &EvaluationContext,
    ) -> bool {
        // Check if objective should be active in current context
        objective
            .context_dependencies
            .iter()
            .all(|dep| self.evaluate_context_dependency(dep, context))
    }

    fn evaluate_context_dependency(
        &self,
        dependency: &ContextDependency,
        context: &EvaluationContext,
    ) -> bool {
        // Evaluate context dependency - simplified implementation
        true
    }
}

// Error handling
#[derive(Debug)]
pub enum ObjectiveError {
    ObjectiveNotFound(String),
    ObjectiveAlreadyExists(String),
    ConstraintNotFound(String),
    InvalidObjective(String),
    InvalidConstraint(String),
    InvalidWeight(String),
    EvaluationFailed(String),
    OptimizationFailed(String),
    ValidationFailed(String),
    LockError,
    ConfigurationError(String),
    ImportExportError(String),
    CompatibilityError(String),
    ConflictError(String),
}

impl std::fmt::Display for ObjectiveError {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        match self {
            ObjectiveError::ObjectiveNotFound(id) => write!(f, "Objective not found: {}", id),
            ObjectiveError::ObjectiveAlreadyExists(id) => {
                write!(f, "Objective already exists: {}", id)
            }
            ObjectiveError::ConstraintNotFound(id) => write!(f, "Constraint not found: {}", id),
            ObjectiveError::InvalidObjective(msg) => write!(f, "Invalid objective: {}", msg),
            ObjectiveError::InvalidConstraint(msg) => write!(f, "Invalid constraint: {}", msg),
            ObjectiveError::InvalidWeight(msg) => write!(f, "Invalid weight: {}", msg),
            ObjectiveError::EvaluationFailed(msg) => {
                write!(f, "Objective evaluation failed: {}", msg)
            }
            ObjectiveError::OptimizationFailed(msg) => {
                write!(f, "Multi-objective optimization failed: {}", msg)
            }
            ObjectiveError::ValidationFailed(msg) => write!(f, "Validation failed: {}", msg),
            ObjectiveError::LockError => write!(f, "Failed to acquire lock"),
            ObjectiveError::ConfigurationError(msg) => write!(f, "Configuration error: {}", msg),
            ObjectiveError::ImportExportError(msg) => write!(f, "Import/export error: {}", msg),
            ObjectiveError::CompatibilityError(msg) => write!(f, "Compatibility error: {}", msg),
            ObjectiveError::ConflictError(msg) => write!(f, "Conflict error: {}", msg),
        }
    }
}

impl std::error::Error for ObjectiveError {}

// Placeholder implementations for supporting structures
// (Due to space constraints, providing abbreviated versions)

#[derive(Debug, Default)]
pub struct ObjectiveManagerConfig;
#[derive(Debug, Default)]
pub struct ObjectiveRegistryConfig;
#[derive(Debug, Default)]
pub struct ParetoFrontAnalyzer;
#[derive(Debug, Default)]
pub struct ObjectiveFunctionEvaluator;
#[derive(Debug, Default)]
pub struct ConstraintSatisfactionChecker;
#[derive(Debug, Default)]
pub struct TradeoffAnalyzer;
#[derive(Debug, Default)]
pub struct ObjectiveDecompositionSystem;
#[derive(Debug, Default)]
pub struct DynamicObjectiveAdjustment;
#[derive(Debug, Default)]
pub struct SolutionArchiveManager;
#[derive(Debug, Default)]
pub struct ObjectiveMetricsTracker;
#[derive(Debug, Default)]
pub struct ObjectiveVisualizationSystem;

// Additional supporting structures (abbreviated for space)
#[derive(Debug, Default, Clone)]
pub struct ObjectiveHierarchy;
#[derive(Debug, Default)]
pub struct DependencyGraph;
#[derive(Debug, Default, Clone)]
pub struct ObjectiveTemplate;
#[derive(Debug, Default)]
pub struct ObjectiveFactory;
#[derive(Debug, Default)]
pub struct ObjectiveValidationFramework;
#[derive(Debug, Default)]
pub struct ObjectiveVersioningSystem;
#[derive(Debug, Default, Clone)]
pub struct MeasurementConfiguration;
#[derive(Debug, Default, Clone)]
pub struct ObjectiveBounds;
#[derive(Debug, Default, Clone)]
pub struct SensitivityAnalysis;
#[derive(Debug, Default, Clone)]
pub struct ObjectiveHistoryEntry;
#[derive(Debug, Default, Clone, Copy)]
pub struct ObjectivePriority;
#[derive(Debug, Default, Clone)]
pub struct ContextDependency;
#[derive(Debug, Default, Clone)]
pub struct ObjectiveQualityAssessment;
#[derive(Debug, Default, Clone)]
pub struct ObjectiveMetadata;
#[derive(Debug, Default, Clone)]
pub struct ObjectiveValidationRule;
#[derive(Debug, Default, Clone)]
pub struct SuccessCriterion;
#[derive(Debug, Default, Clone)]
pub struct FailureCondition;
#[derive(Debug, Default, Clone, Copy)]
pub struct TrajectoryPath;
#[derive(Debug, Default, Clone)]
pub struct OptimizationCondition;
#[derive(Debug, Default, Clone)]
pub struct ConstraintValue;
#[derive(Debug, Default, Clone, Copy)]
pub struct ConstraintStrictness;
#[derive(Debug, Default, Clone)]
pub struct PenaltyFunction;
#[derive(Debug, Default, Clone)]
pub struct ActivationCondition;
#[derive(Debug, Default, Clone)]
pub struct ConstraintDependency;
#[derive(Debug, Default, Clone)]
pub struct TemporalConstraintProperties;
#[derive(Debug, Default, Clone)]
pub struct ConstraintValidationConfig;
#[derive(Debug, Default, Clone)]
pub struct ConstraintViolation;
#[derive(Debug, Default, Clone)]
pub struct ConstraintAdaptationRule;

// Additional trait and implementation stubs
pub trait MultiObjectiveAlgorithm: std::fmt::Debug + Send + Sync {
    fn optimize(
        &mut self,
        session: &mut OptimizationSession,
    ) -> Result<OptimizationResult, ObjectiveError>;
    fn get_name(&self) -> &str;
    fn get_parameters(&self) -> HashMap<String, f64>;
}

// Many more supporting structures would be implemented here for a complete system
// This shows the core architecture and main functionality

impl ConstraintValue {
    pub const Single: fn(f64) -> Self = |_| Self;
    pub const Range: fn(f64, f64) -> Self = |_, _| Self;
}

impl DependencyGraph {
    fn new() -> Self {
        Self
    }
    fn add_dependency(&mut self, from: &str, to: &str) -> Result<(), ObjectiveError> {
        Ok(())
    }
}

impl ConstraintManager {
    fn new(config: ConstraintManagerConfig) -> Self {
        Self
    }
    fn register_constraint(
        &mut self,
        constraint: ObjectiveConstraint,
    ) -> Result<(), ObjectiveError> {
        Ok(())
    }
    fn check_constraints(
        &self,
        params: &HashMap<String, f64>,
        context: &EvaluationContext,
    ) -> Result<ConstraintSatisfactionResult, ObjectiveError> {
        Ok(ConstraintSatisfactionResult::default())
    }
    fn get_all_constraints(&self) -> Vec<ObjectiveConstraint> {
        Vec::new()
    }
    fn detect_infeasible_constraints(
        &self,
        constraints: &[ObjectiveConstraint],
    ) -> Result<Vec<String>, ObjectiveError> {
        Ok(Vec::new())
    }
    fn detect_redundant_constraints(
        &self,
        constraints: &[ObjectiveConstraint],
    ) -> Result<Vec<String>, ObjectiveError> {
        Ok(Vec::new())
    }
    fn export_constraints(&self) -> Result<Vec<ObjectiveConstraint>, ObjectiveError> {
        Ok(Vec::new())
    }
    fn count_constraints(&self) -> usize {
        0
    }
    fn get_satisfaction_metrics(&self) -> ConstraintMetrics {
        ConstraintMetrics::default()
    }
}

impl ObjectiveFunctionEvaluator {
    fn new(config: ObjectiveEvaluatorConfig) -> Self {
        Self
    }
    fn evaluate_objective(
        &self,
        objective: &OptimizationObjective,
        params: &HashMap<String, f64>,
        context: &EvaluationContext,
    ) -> Result<f64, ObjectiveError> {
        Ok(0.0)
    }
    fn validate_function(&self, function: &ObjectiveFunction) -> Result<(), ObjectiveError> {
        Ok(())
    }
}

impl ObjectiveMetricsTracker {
    fn new(config: ObjectiveMetricsConfig) -> Self {
        Self
    }
    fn initialize_objective_tracking(&mut self, objective_id: &str) -> Result<(), ObjectiveError> {
        Ok(())
    }
    fn record_evaluation(
        &mut self,
        objective_results: &HashMap<String, f64>,
        constraint_results: &ConstraintSatisfactionResult,
    ) -> Result<(), ObjectiveError> {
        Ok(())
    }
    fn get_comprehensive_metrics(&self) -> ObjectiveMetrics {
        ObjectiveMetrics::default()
    }
    fn get_performance_trends(&self) -> PerformanceTrends {
        PerformanceTrends::default()
    }
}

impl MultiObjectiveEngine {
    fn new(config: MultiObjectiveEngineConfig) -> Self {
        Self
    }
    fn create_session(
        &self,
        config: MultiObjectiveConfig,
    ) -> Result<OptimizationSession, ObjectiveError> {
        Ok(OptimizationSession::default())
    }
    fn optimize(
        &self,
        session: &mut OptimizationSession,
    ) -> Result<MultiObjectiveOptimizationResult, ObjectiveError> {
        Ok(MultiObjectiveOptimizationResult::default())
    }
    fn get_current_pareto_front(&self) -> Result<ParetoFront, ObjectiveError> {
        Ok(ParetoFront::default())
    }
    fn update_weights(&mut self, weights: &HashMap<String, f32>) -> Result<(), ObjectiveError> {
        Ok(())
    }
    fn start_interactive_session(
        &mut self,
        config: InteractiveOptimizationConfig,
    ) -> Result<InteractiveSession, ObjectiveError> {
        Ok(InteractiveSession::default())
    }
}

impl ParetoFrontAnalyzer {
    fn new(config: ParetoAnalyzerConfig) -> Self {
        Self
    }
    fn analyze_front(&self, front: &ParetoFront) -> Result<ParetoAnalysis, ObjectiveError> {
        Ok(ParetoAnalysis::default())
    }
    fn find_compromise_solutions(
        &self,
        front: &ParetoFront,
        preferences: &UserPreferences,
    ) -> Result<Vec<ParetoSolution>, ObjectiveError> {
        Ok(Vec::new())
    }
    fn get_front_metrics(&self) -> ParetoMetrics {
        ParetoMetrics::default()
    }
}

impl SolutionArchiveManager {
    fn new(config: SolutionArchiveConfig) -> Self {
        Self
    }
    fn add_solutions(&mut self, solutions: &[ParetoSolution]) -> Result<(), ObjectiveError> {
        Ok(())
    }
    fn export_solutions(&self) -> Result<SolutionArchive, ObjectiveError> {
        Ok(SolutionArchive::default())
    }
    fn import_solutions(&mut self, archive: SolutionArchive) -> Result<(), ObjectiveError> {
        Ok(())
    }
    fn count_solutions(&self) -> usize {
        0
    }
    fn get_statistics(&self) -> SolutionStatistics {
        SolutionStatistics::default()
    }
}

// Additional default implementations for placeholder structures
#[derive(Debug, Default)]
pub struct ConstraintManagerConfig;
#[derive(Debug, Default)]
pub struct ObjectiveEvaluatorConfig;
#[derive(Debug, Default)]
pub struct ObjectiveMetricsConfig;
#[derive(Debug, Default)]
pub struct MultiObjectiveEngineConfig;
#[derive(Debug, Default)]
pub struct ParetoAnalyzerConfig;
#[derive(Debug, Default)]
pub struct SolutionArchiveConfig;
#[derive(Debug, Default)]
pub struct EvaluationContext;
#[derive(Debug, Default)]
pub struct ObjectiveEvaluationResult;
#[derive(Debug)]
pub struct ConstraintSatisfactionResult {
    pub total_penalty: f64,
    pub satisfaction_rate: f32,
}
#[derive(Debug, Default)]
pub struct AggregateMetrics {
    pub weighted_objective_score: f64,
    pub constraint_violation_penalty: f64,
    pub overall_fitness: f64,
}
#[derive(Debug, Default)]
pub struct EvaluationMetadata;
#[derive(Debug, Default)]
pub struct EvaluationQualityAssessment {
    pub objective_quality: f32,
    pub assessment_confidence: f32,
    pub assessment_reliability: f32,
}
#[derive(Debug, Default)]
pub struct MultiObjectiveConfig;
#[derive(Debug, Default)]
pub struct MultiObjectiveResult;
#[derive(Debug, Default)]
pub struct TradeoffContext;
#[derive(Debug, Default)]
pub struct TradeoffAnalysis;
#[derive(Debug, Default)]
pub struct DecompositionConfig;
#[derive(Debug, Default)]
pub struct AdjustmentContext;
#[derive(Debug, Default)]
pub struct UserPreferences;
#[derive(Debug, Default)]
pub struct InteractiveOptimizationConfig;
#[derive(Debug, Default)]
pub struct InteractiveSession;
#[derive(Debug, Default)]
pub struct ConsistencyReport {
    pub objective_conflicts: Vec<ObjectiveConflict>,
    pub consistency_score: f32,
    pub conflict_resolution_suggestions: Vec<String>,
}
#[derive(Debug, Default)]
pub struct ObjectiveConfigurationExport;
#[derive(Debug, Default)]
pub struct ObjectiveConfigurationImport;
#[derive(Debug, Default)]
pub struct ImportReport {
    pub successful_objectives: Vec<String>,
    pub failed_objectives: Vec<String>,
    pub warnings: Vec<String>,
    pub import_summary: String,
}
#[derive(Debug, Default)]
pub struct ObjectiveAnalyticsDashboard;
#[derive(Debug, Default)]
pub struct OptimizationSession;
#[derive(Debug, Default)]
pub struct MultiObjectiveOptimizationResult;
#[derive(Debug, Default)]
pub struct ParetoAnalysis;
#[derive(Debug, Default)]
pub struct MultiObjectiveRecommendation;
#[derive(Debug, Default)]
pub struct ComputationalResources;
#[derive(Debug, Default)]
pub struct ObjectiveConflict;
#[derive(Debug, Default)]
pub struct CompatibilityIssue;
#[derive(Debug, Default)]
pub struct ExportMetadata;
#[derive(Debug, Default)]
pub struct DashboardRecommendation;
#[derive(Debug, Default)]
pub struct ConstraintMetrics;
#[derive(Debug, Default)]
pub struct ObjectiveMetrics;
#[derive(Debug, Default)]
pub struct PerformanceTrends;
#[derive(Debug, Default)]
pub struct ParetoMetrics;
#[derive(Debug, Default)]
pub struct SolutionArchive;
#[derive(Debug, Default)]
pub struct SolutionStatistics;
#[derive(Debug, Default, Copy, Clone)]
pub struct RecommendationType;
#[derive(Debug, Default, Copy, Clone)]
pub struct ConflictType;
#[derive(Debug, Default, Copy, Clone)]
pub struct ConflictSeverity;
#[derive(Debug, Default)]
pub struct ResolutionSuggestion;
#[derive(Debug, Default, Copy, Clone)]
pub struct SuggestionType;
#[derive(Debug, Default, Copy, Clone)]
pub struct ImplementationEffort;

// Enum implementations
impl RecommendationType {
    pub const KneeSolution: Self = Self;
    pub const FocusObjective: Self = Self;
}

impl ConflictSeverity {
    pub const High: Self = Self;
    pub const Medium: Self = Self;
    pub const Low: Self = Self;
}

impl SuggestionType {
    pub const WeightAdjustment: Self = Self;
    pub const ObjectiveReformulation: Self = Self;
}

impl ImplementationEffort {
    pub const Low: Self = Self;
    pub const Medium: Self = Self;
    pub const High: Self = Self;
}

impl AggregateMetrics {
    fn new() -> Self {
        Self {
            weighted_objective_score: 0.0,
            constraint_violation_penalty: 0.0,
            overall_fitness: 0.0,
        }
    }
}

impl EvaluationQualityAssessment {
    fn new() -> Self {
        Self {
            objective_quality: 0.0,
            assessment_confidence: 0.0,
            assessment_reliability: 0.0,
        }
    }
}

impl ConsistencyReport {
    fn new() -> Self {
        Self {
            objective_conflicts: Vec::new(),
            consistency_score: 0.0,
            conflict_resolution_suggestions: Vec::new(),
        }
    }
}

impl ImportReport {
    fn new() -> Self {
        Self {
            successful_objectives: Vec::new(),
            failed_objectives: Vec::new(),
            warnings: Vec::new(),
            import_summary: String::new(),
        }
    }
}

impl ConstraintSatisfactionResult {
    fn new() -> Self {
        Self {
            total_penalty: 0.0,
            satisfaction_rate: 0.0,
        }
    }
}

impl Default for ConstraintSatisfactionResult {
    fn default() -> Self {
        Self {
            total_penalty: 0.0,
            satisfaction_rate: 1.0,
        }
    }
}

impl Default for ParetoFront {
    fn default() -> Self {
        Self {
            solutions: Vec::new(),
            generation: 0,
            quality_metrics: ParetoQualityMetrics::default(),
            dominance_matrix: DominanceMatrix::default(),
            reference_points: Vec::new(),
            ideal_point: Vec::new(),
            nadir_point: Vec::new(),
            approximation_quality: ApproximationQuality::default(),
            stability_measures: FrontStabilityMeasures::default(),
            visualization_data: FrontVisualizationData::default(),
            statistical_analysis: FrontStatisticalAnalysis::default(),
        }
    }
}

// Additional placeholder structures for complete compilation
#[derive(Debug, Default)]
pub struct ParetoQualityMetrics;
#[derive(Debug, Default)]
pub struct DominanceMatrix;
#[derive(Debug, Default)]
pub struct ReferencePoint;
#[derive(Debug, Default)]
pub struct ApproximationQuality;
#[derive(Debug, Default)]
pub struct FrontStabilityMeasures;
#[derive(Debug, Default)]
pub struct FrontVisualizationData;
#[derive(Debug, Default)]
pub struct FrontStatisticalAnalysis;
#[derive(Debug, Default)]
pub struct ConstraintSatisfactionStatus;
#[derive(Debug, Default)]
pub struct ResourceRequirements;
#[derive(Debug, Default)]
pub struct SolutionRiskAssessment;
#[derive(Debug, Default)]
pub struct SolutionMetadata;
#[derive(Debug, Default)]
pub struct SolutionValidationResults;
#[derive(Debug, Default)]
pub struct UserFeedback;

// This represents the comprehensive objectives and constraints module architecture