pumpkin-core 0.4.0

The core of the Pumpkin constraint programming solver.
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157

use std::ops::ControlFlow;

use super::OptimisationProcedure;
use super::solution_callback::SolutionCallback;
use crate::Solver;
use crate::branching::Brancher;
use crate::conflict_resolving::ConflictResolver;
use crate::optimisation::OptimisationDirection;
use crate::predicate;
use crate::results::OptimisationResult;
use crate::results::ProblemSolution;
use crate::results::SatisfactionResult;
use crate::results::SatisfactionResultUnderAssumptions;
use crate::results::Solution;
use crate::termination::TerminationCondition;
use crate::variables::IntegerVariable;

/// Implements the linear SAT-UNSAT (LSU) optimisation procedure.
#[derive(Debug, Clone, Copy)]
pub struct LinearSatUnsat<Var, Callback> {
    direction: OptimisationDirection,
    objective: Var,
    solution_callback: Callback,
}

impl<Var, Callback> LinearSatUnsat<Var, Callback> {
    /// Create a new instance of [`LinearSatUnsat`].
    pub fn new(
        direction: OptimisationDirection,
        objective: Var,
        solution_callback: Callback,
    ) -> Self {
        Self {
            direction,
            objective,
            solution_callback,
        }
    }

    fn run_optimisation<B, R>(
        &mut self,
        brancher: &mut B,
        termination: &mut impl TerminationCondition,
        resolver: &mut R,
        solver: &mut Solver,
        objective: impl IntegerVariable,
        mut best_solution: Solution,
    ) -> OptimisationResult<Callback::Stop>
    where
        Callback: SolutionCallback<B, R>,
        B: Brancher,
        R: ConflictResolver,
    {
        loop {
            let callback_result = self.solution_callback.on_solution_callback(
                solver,
                best_solution.as_reference(),
                brancher,
                resolver,
            );

            if let ControlFlow::Break(stop) = callback_result {
                return OptimisationResult::Stopped(best_solution, stop);
            }

            let best_objective_value = best_solution.get_integer_value(objective.clone());

            let conclusion = {
                let solve_result = solver.satisfy_under_assumptions(
                    brancher,
                    termination,
                    resolver,
                    &[predicate![objective <= best_objective_value - 1]],
                );

                match solve_result {
                    SatisfactionResultUnderAssumptions::Satisfiable(satisfiable) => {
                        best_solution = satisfiable.solution().into();
                        None
                    }
                    SatisfactionResultUnderAssumptions::UnsatisfiableUnderAssumptions(_) => {
                        Some(OptimisationResult::Optimal(best_solution.clone()))
                    }
                    SatisfactionResultUnderAssumptions::Unsatisfiable(_) => unreachable!(
                        "If the problem is unsatisfiable here, it would have been unsatisifable in the initial solve."
                    ),
                    SatisfactionResultUnderAssumptions::Unknown(_) => {
                        Some(OptimisationResult::Satisfiable(best_solution.clone()))
                    }
                }
            };

            match conclusion {
                Some(OptimisationResult::Optimal(solution)) => {
                    return OptimisationResult::Optimal(solution);
                }
                Some(result) => return result,
                None => {}
            }
        }
    }
}

impl<Var, Callback, B, R> OptimisationProcedure<B, R, Callback> for LinearSatUnsat<Var, Callback>
where
    Var: IntegerVariable,
    B: Brancher,
    R: ConflictResolver,
    Callback: SolutionCallback<B, R>,
    Callback::Stop: std::fmt::Debug,
{
    fn optimise(
        &mut self,
        brancher: &mut B,
        termination: &mut impl TerminationCondition,
        resolver: &mut R,
        solver: &mut Solver,
    ) -> OptimisationResult<Callback::Stop> {
        let objective = match self.direction {
            OptimisationDirection::Maximise => self.objective.scaled(-1),
            OptimisationDirection::Minimise => self.objective.scaled(1),
        };

        // First we will solve the satisfaction problem without constraining the objective.
        let initial_solution: Solution = match solver.satisfy(brancher, termination, resolver) {
            SatisfactionResult::Satisfiable(satisfiable) => satisfiable.solution().into(),
            SatisfactionResult::Unsatisfiable(_, _, _) => return OptimisationResult::Unsatisfiable,
            SatisfactionResult::Unknown(_, _, _) => return OptimisationResult::Unknown,
        };

        let optimisation_result = self.run_optimisation(
            brancher,
            termination,
            resolver,
            solver,
            objective.clone(),
            initial_solution,
        );

        match optimisation_result {
            OptimisationResult::Optimal(solution) => {
                let objective_value = solution.get_integer_value(objective.clone());
                solver.conclude_proof_dual_bound(predicate![objective >= objective_value]);

                OptimisationResult::Optimal(solution)
            }
            OptimisationResult::Unsatisfiable => {
                solver.conclude_proof_unsat();
                OptimisationResult::Unsatisfiable
            }

            result @ (OptimisationResult::Satisfiable(_)
            | OptimisationResult::Stopped(_, _)
            | OptimisationResult::Unknown) => result,
        }
    }
}