Module scalarization_methods 

Scalarization Methods for Multi-Objective Optimization

This module provides various scalarization techniques for converting multi-objective optimization problems into single-objective problems. These methods enable the systematic exploration of trade-offs between conflicting objectives.

Key Features

• Weighted Sum Method: Simple linear combination of objectives with user-defined weights
• Epsilon-Constraint Method: Optimize one objective while constraining others
• Achievement Scalarizing Function: Reference point-based optimization
• Augmented Weighted Tchebycheff: Improved Tchebycheff scalarization
• Normalized Normal Constraint: Advanced constraint handling for Pareto front generation
• Problem Generation: Systematic generation of scalarized subproblems

Structs

ScalarizationConfig

Configuration for scalarization optimizer

ScalarizationOptimizer

Scalarization optimizer for converting multi-objective problems to single-objective

ScalarizationOptimizerTrained

Trained state for scalarization optimizer

Enums

ScalarizationMethod

Scalarization method types for multi-objective optimization