Recuit simulé ajout de remove et insert dépendant de la progression du recuit + autoriser le remove à couter quedalle au début puis un max et de même pour les violation d'intervales (pour l'instant une seule violation autorisée et compatibilisée à la detection)

.gitignore

@@ -1,2 +1,4 @@
 build
 lib
+Data
+.cache

src/OrdoCorr/.vscode/CurrentVersionLabTesting.code-workspace

@@ -1,37 +0,0 @@
-{
-	"folders": [
-		{
-			"path": "../../.."
-		}
-	],
-	"settings": {},
-	"launch": {
-		"version": "0.2.0",
-		"configurations": [
-		    {
-            "type": "lldb",
-            "request": "launch",
-            "name": "Debug",
-            "program": "${workspaceFolder}/build/bin/Debug/OrdonnancementCorrectif",
-            "args": ["--solve", "-TRACKPLANS", "1_3_10_100_100_0.json"],
-            "cwd": "${workspaceFolder}/build/bin/Debug/"
-        	},
-			{
-            "type": "lldb",
-            "request": "launch",
-            "name": "DebugPrevRep",
-            "program": "${workspaceFolder}/build/bin/Debug/OrdonnancementCorrectif",
-            "args": ["--solve", "-PREVREP", "1_6_20_150_50_2.json"],
-            "cwd": "${workspaceFolder}/build/bin/Debug/"
-        	},
-			{
-            "type": "lldb",
-            "request": "launch",
-            "name": "DebugIns",
-            "program": "${workspaceFolder}/build/bin/Debug/InstanceGenerator",
-            "args": [],
-            "cwd": "${workspaceFolder}/build/bin/Debug/"
-        	}
-		]
-	}
-}

src/OrdoCorr/.vscode/launch.json

@@ -1,17 +0,0 @@
-{
-    // Use IntelliSense to learn about possible attributes.
-    // Hover to view descriptions of existing attributes.
-    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
-    "version": "0.2.0",
-    "configurations": [
-        {
-            "type": "lldb",
-            "request": "launch",
-            "name": "Debug",
-            "program": "${workspaceFolder}/build/bin/Debug/OrdonnancementCorrectif",
-            "args": ["--solve", "-HEURISTIC", "soutenance.json"],
-            "cwd": "${workspaceFolder}/build/bin/Debug/"
-        }
-
-    ]
-}

src/OrdoCorr/Solver/TrackPlansILP/Penalty.hpp

@@ -0,0 +1,59 @@
+#ifndef PENALTY_HPP
+#define PENALTY_HPP
+#include <unordered_map>
+#include <string>
+
+namespace solverlib {
+
+    enum class EPenaltyType {
+        TIME_WINDOW_OVERRUN,   // job dépasse sa fenêtre
+    };
+
+    struct Penalty {
+        std::unordered_map<EPenaltyType, double> components;
+
+        void add(EPenaltyType type, double value) {
+            components[type] += value;
+        }
+
+        void subtract(EPenaltyType type, double value) {
+            components[type] = std::max(0.0, components[type] - value);
+        }
+
+        // Coût agrégé pondéré — les lambdas sont injectés depuis l'extérieur
+        double weighted(const std::unordered_map<EPenaltyType, double>& lambdas) const {
+            double total = 0.0;
+            for (auto& [type, val] : components)
+            {
+                auto it = lambdas.find(type);
+                if (it != lambdas.end())
+                    total += it->second * val;
+            }
+            return total;
+        }
+
+        double total() const {
+            double sum = 0.0;
+            for (auto& [_, v] : components) sum += v;
+            return sum;
+        }
+
+        bool isFeasible() const { return total() == 0.0; }
+
+        Penalty operator+(const Penalty& o) const {
+            Penalty res = *this;
+            for (auto& [type, val] : o.components)
+                res.components[type] += val;
+            return res;
+        }
+
+        Penalty operator-(const Penalty& o) const {
+            Penalty res = *this;
+            for (auto& [type, val] : o.components)
+                res.components[type] = std::max(0.0, res.components[type] - val);
+            return res;
+        }
+    };
+}
+
+#endif

src/OrdoCorr/Solver/TrackPlansILP/SimulatedAnnealing.cpp

@@ -1,6 +1,7 @@
 #include "SimulatedAnnealing.hpp"
 #include "../PseCarlierRivreau/omp.h"
 #include "DynamicProgramming.hpp"
+#include "Penalty.hpp"
 #include "Solution.hpp"
 #include "TrackPlan.hpp"
 #include <algorithm>
@@ -10,24 +11,28 @@
 #include <iterator>
 #include <optional>
 #include <random>
+#include <stdexcept>
 #include <string>
 #include <utility>
 #include <vector>
 #include "Random.hpp"
 #include "sourceSolTrPlan.hpp"
 
+
 namespace solverlib {
     using namespace random;
 
     bool StatSimulatedAnnealing::activate = true;
     bool SimulatedAnnealing::withDynProg = false;
+    bool SimulatedAnnealing::authorizeInfeasible = true;
 
+    constexpr double decreaseFunction(double p){return std::exp(-0.75*(1.0-p));};
 
     std::unordered_map<EMovingOperators, std::string> StatSimulatedAnnealing::names = {
-        {EMovingOperators::CHANGE_MODE_WITHOUT_CARLIER, "CHANGE_MODE"},
+        {EMovingOperators::CHANGE_MODE, "CHANGE_MODE"},
-        {EMovingOperators::INSERT_WITHOUT_CARLIER, "INSERT"},
+        {EMovingOperators::INSERT, "INSERT"},
-        {EMovingOperators::REMOVE_WITHOUT_CARLIER, "REMOVE"},
+        {EMovingOperators::REMOVE, "REMOVE"},
-        {EMovingOperators::SWAP_WITHOUT_CARLIER, "SWAP"},
+        {EMovingOperators::SWAP, "SWAP"},
         {EMovingOperators::SWAP_WITHIN_INTERVAL, "SWAP_WITHIN_SEQUENCE"},
         {EMovingOperators::DYN_PROG, "DYN_PROG"},
         {EMovingOperators::MOVE, "MOVE"}
@@ -37,7 +42,11 @@ namespace solverlib {
     SimulatedAnnealing::SimulatedAnnealing(std::unordered_map<unsigned short, Decision>& decs, std::shared_ptr<modellib::STFMockInstance> mock, ESourceTrackPlan source)
     {
         randomEngine = solverlib::random::makeEngine();
+        maxCostOfJob = (*std::max_element(STFMockInstance::jobs.begin(), STFMockInstance::jobs.end(), [&](auto op1, auto op2){return op1->getPoidsRetard() < op2->getPoidsRetard();}))->getPoidsRetard();
+        setPenaltyWeights();
         addSolutionToPool(decs, mock, source);
+        for (unsigned int i = 0; i< STFMockInstance::machines.size(); ++i)
+            solutions[0].penaltyPerMachine[i] = Penalty{};
     }
 
     void SimulatedAnnealing::addSolutionToPool(std::unordered_map<unsigned short, Decision>& decs, std::shared_ptr<modellib::STFMockInstance> mock, ESourceTrackPlan source, bool isPutFirst)
@@ -73,58 +82,24 @@ namespace solverlib {
         return {cost, diagCost};
     }
 
-    std::pair<unsigned int, unsigned int> SimulatedAnnealing::getCostOfSequence(std::vector<std::pair<unsigned short, decision>>& jobsSeq)
+    EMovingOperators SimulatedAnnealing::pick_operator() {
-    {
+        double p = progress();
-        unsigned int cost = 0;
-        unsigned int costDiag = 0;
-        for(auto& el : jobsSeq)
-        {
-            cost += STFMockInstance::jobs[el.first]->getPoidsRetard()*el.second.lastCreneau.first;
-            costDiag += STFMockInstance::jobs[el.first]->getPoidsRejet()*el.second.rejected;
-        }
-        return {cost, costDiag};
-    }
-
-
-    // tire un opérateur uniformément
-    EMovingOperators SimulatedAnnealing::pick_operator(double temp, double tmax) {
-        int N = withDynProg ? static_cast<int>(EMovingOperators::DYN_PROG)+1 : static_cast<int>(EMovingOperators::MOVE)+1;
-        std::vector<float> weights(N, 1);
 
+        float w_remove = static_cast<float>(2*std::max(0.0,1.0 - decreaseFunction(p)));
+        float w_insert = static_cast<float>(2*std::min(1.0, decreaseFunction(p)));
         std::vector<float> base_weights = {
-            1.0f,   
+            1,   
-            1.0f,   
+            w_insert,   
-            1.0f,
+            w_remove,
-            1.0f,   
+            1,   
-            1.0f,   
+            1,   
-            1.0f    
+            1    
             // DYN_PROG ajouté si besoin
         };
-        if (withDynProg) base_weights.push_back(0.5f); // DYN_PROG
+        if (withDynProg) base_weights.push_back(1.0f); // DYN_PROG
 
-        const float remove_base = 1.0f;  // poids max du remove (en début de recuit)
-        const float t = temp / tmax;  // 1.0 → 0.0
-
-        // Poids remove
-        const float w_remove = remove_base * t;
-
-        // Le budget récupéré est redistribué proportionnellement aux autres
-        const float base_sum = std::accumulate(base_weights.begin(), base_weights.end(), 0.0f);
-        const float bonus = remove_base * (1.0f - t);
-
-        // Index du REMOVE dans ton enum — à adapter
-        constexpr int REMOVE_IDX = 2;
-
-        for (int i = 0; i < N; ++i) {
-            if (i == REMOVE_IDX) {
-                weights[i] = w_remove;
-            } else {
-                weights[i] = base_weights[i] + bonus * (base_weights[i] / base_sum);
-            }
-        }
         return static_cast<EMovingOperators>(
-            //std::uniform_int_distribution<int>(0, N)(randomEngine)
+            std::discrete_distribution<int>(base_weights.begin(), base_weights.end())(randomEngine)
-            std::discrete_distribution<int>(weights.begin(), weights.end())(randomEngine)
         );
     }
 
@@ -133,10 +108,10 @@ namespace solverlib {
     {
         switch (op)
         {
-            case EMovingOperators::SWAP_WITHOUT_CARLIER:                    return move_swap_WC(current);
+            case EMovingOperators::SWAP:                    return move_swap_WC(current);
-            case EMovingOperators::INSERT_WITHOUT_CARLIER:                  return move_insert_WC(current);
+            case EMovingOperators::INSERT:                  return move_insert_WC(current);
-            case EMovingOperators::REMOVE_WITHOUT_CARLIER:                  return move_remove_WC(current);
+            case EMovingOperators::REMOVE:                  return move_remove_WC(current);
-            case EMovingOperators::CHANGE_MODE_WITHOUT_CARLIER:             return move_change_mode_WC(current);
+            case EMovingOperators::CHANGE_MODE:             return move_change_mode_WC(current);
             case EMovingOperators::SWAP_WITHIN_INTERVAL:                    return move_swap_within_interval(current);
             case EMovingOperators::MOVE:                                    return move_move_WC(current);
             case EMovingOperators::DYN_PROG:                                return move_dynprog(current);                       
@@ -150,16 +125,22 @@ namespace solverlib {
     {
         SASolution current  = solutions[0];
         SASolution best     = solutions[0];
+        current.fictiveCost = current.cost;
+        best.fictiveCost = current.cost;
+
+        Tmax = T_max;
         double   cost_cur = current.cost;
         double   cost_best= cost_cur;
-        double   T        = T_max;
+        T = Tmax;
+        Tmin = T_min;
+        rate = cooling_rate;
         std::uniform_real_distribution<double> uniform(0.0, 1.0);
 
-        while (T > T_min + 10e-6)
+        while (T > Tmin + 10e-6)
         {
             for (int i = 0; i < iterations_per_temp; ++i)
             {
-                EMovingOperators op = pick_operator(T, T_max);
+                EMovingOperators op = pick_operator();
                 stats.addUsed(op);
                 auto neighbor = apply_operator(current, op);
 
@@ -167,23 +148,33 @@ namespace solverlib {
 
                 auto costs_neighbor = std::make_pair(neighbor->cost, neighbor->diagCost);
 
-                double delta = costs_neighbor.first - cost_cur;
+                double delta = effectiveCost(*neighbor) - effectiveCost(current);
+                double diff = (double)neighbor->cost - (double)current.cost;
 
+                if(neighbor->penalty.isFeasible())
                     stats.addFeas(op);
+
                 if(delta <= 0)
                     stats.addImproved(op);
 
+                if(diff <= 0 && neighbor->penalty.isFeasible())
+                    stats.addImprovedReal(op);
+
+                if(!neighbor->penalty.isFeasible())
+                    stats.addInfeasible(op);
+            
                 if(delta > 0)
                 {
-                    stats.addFailInfo(op, getP(delta, T, op), delta, T);   
+                    stats.addFailInfo(op, getP(delta, op), diff, delta, T, neighbor->penalty.isFeasible());   
                 }
+                //TODO AJOUTER AUTORISER AVEC PENALITE LES INFEASABLES => NECESSITE DE METTRE À JOUR LA GENERATION TRACK PLAN POUR LE ILP ET IGNORER LES TRACKPLANS INF
 
-                if (delta < 0 || uniform(randomEngine) < getP(delta, T, op))
+                if (delta < 0 || uniform(randomEngine) < getP(delta, op))
                 {
                     current  = std::move(*neighbor);
                     cost_cur = costs_neighbor.first;
 
-                    if (cost_cur < cost_best) {
+                    if (current.penalty.isFeasible() && cost_cur < cost_best) {
                         best      = current;
                         cost_best = cost_cur;
                     }
@@ -201,22 +192,43 @@ namespace solverlib {
         return best;
     }
 
-    double SimulatedAnnealing::getP(double delta, double temperature, EMovingOperators op)
+    double SimulatedAnnealing::effectiveCost(const SASolution& s) const {
+        return s.fictiveCost + s.penalty.weighted(effectiveLambdas());
+    }
+
+    std::unordered_map<EPenaltyType, double> SimulatedAnnealing::effectiveLambdas() const {
+        double p = progress();
+        return {
+            {EPenaltyType::TIME_WINDOW_OVERRUN,  std::exp(8*(p-0.2))-0.8},
+        };
+    }
+
+    double SimulatedAnnealing::progress() const {
+        //return 1.0 - (T - Tmin) / (Tmax - Tmin); // 0 au début, 1 à la fin
+        return 1.0 - (std::log(T) - std::log(Tmin)) / (std::log(Tmax) - std::log(Tmin));
+    }
+
+    double SimulatedAnnealing::fictiveCostExcluded(unsigned short op_id) const {
+        return decreaseFunction(progress()) * MAXIMUM_TIME_OFFSET
+            * STFMockInstance::jobs[op_id]->getPoidsRetard();
+    }
+
+
+    double SimulatedAnnealing::getP(double delta, EMovingOperators op)
     {
         switch (op) {
-            case EMovingOperators::SWAP_WITHOUT_CARLIER:
+            case EMovingOperators::SWAP:
-            case EMovingOperators::INSERT_WITHOUT_CARLIER:
+            case EMovingOperators::INSERT: return std::exp(-delta/(T*50));
-            case EMovingOperators::REMOVE_WITHOUT_CARLIER: return std::exp(-delta/(temperature*100));
+            case EMovingOperators::REMOVE: return std::exp(-delta/(T*50));
-            case EMovingOperators::CHANGE_MODE_WITHOUT_CARLIER:
+            case EMovingOperators::CHANGE_MODE:
             case EMovingOperators::SWAP_WITHIN_INTERVAL:
-            case EMovingOperators::MOVE: return std::exp(-delta/(temperature*10));
+            case EMovingOperators::MOVE: return std::exp(-delta/(T*20));
             case EMovingOperators::DYN_PROG:
           break;
         }
-        return std::exp(-delta/temperature);
+        return std::exp(-delta/T);
     }
 
-
     //OPERATEURS
 
     std::optional<SASolution> SimulatedAnnealing::move_dynprog(const SASolution& sol)
@@ -265,55 +277,48 @@ namespace solverlib {
         auto posA = std::find(seq_swap.begin(), seq_swap.end(), op_a);
         if(posA == seq_swap.end()) return std::nullopt;
         
-        auto lbdBuildSeq = [&](std::vector<unsigned short>& seq) -> std::optional<SASolution> {
+        auto IposA = std::distance(seq_swap.begin(), posA);
-            SASolution neighbor = sol;
-            auto creneauTrack = STFMockInstance::machines[dec_a.empV]->getDispo();
-            unsigned short lastEnd = 0;
-            unsigned int oldCost = 0;
-            unsigned int newCost = 0;
-            for(auto& job : seq)
-            {
-                Decision& dec_neih = neighbor.decisions.at(job);
-                auto creneauJob = mock->trajectoryStops[dec_neih.empR].getDispoStop();
-                auto match = CreneauHoraire::checkSlotsCompatibility(creneauJob, creneauTrack);
-                oldCost += STFMockInstance::jobs[job]->getPoidsRetard()*sol.decisions.at(job).lastCreneau.first;
-                if(match.first)
-                {
-                    if(std::max(match.second.first, lastEnd) + dec_neih.rejected*STFMockInstance::jobs[job]->getDureeDiag() + !dec_neih.rejected*STFMockInstance::jobs[job]->getDuree() > match.second.first + match.second.second)
-                        return std::nullopt;
 
-                    dec_neih.lastCreneau = {
+        // Tirer un index différent de IposA pour le swap
-                        std::max(match.second.first, lastEnd),
+        std::uniform_int_distribution<int> posR(0, (int)seq_swap.size() - 1);
-                        std::max(match.second.first, lastEnd)+ dec_neih.rejected*STFMockInstance::jobs[job]->getDureeDiag() + !dec_neih.rejected*STFMockInstance::jobs[job]->getDuree()
+        int posB = posR(randomEngine);
-                    };
+        while (posB == IposA)
-                    newCost += STFMockInstance::jobs[job]->getPoidsRetard()*dec_neih.lastCreneau.first;
+            posB = posR(randomEngine);
-                    lastEnd = std::max(match.second.first, lastEnd)+ dec_neih.rejected*STFMockInstance::jobs[job]->getDureeDiag() + !dec_neih.rejected*STFMockInstance::jobs[job]->getDuree();
+
-                }
+        auto seqCop = seq_swap;
-                else {
+        std::swap(seqCop[IposA], seqCop[posB]);
-                    return std::nullopt;
+
-                }
+        // Reconstruire le vecteur de décisions dans le bon ordre
-            }
+        std::vector<std::pair<unsigned short, Decision>> jobsSeq;
+        jobsSeq.reserve(seqCop.size());
+        for (auto& job_id : seqCop)
+            jobsSeq.push_back({job_id, sol.decisions.at(job_id)});    
+
+        Penalty oldPen = sol.penaltyPerMachine.count(dec_a.empV)
+            ? sol.penaltyPerMachine.at(dec_a.empV)
+            : Penalty{};
+
+        unsigned int oldCost = 0;
+        for (auto& job_id : seq_swap)
+            oldCost += STFMockInstance::jobs[job_id]->getPoidsRetard()
+                    * sol.decisions.at(job_id).lastCreneau.first;
+
+        Penalty newPen; bool feasible = true;
+        auto res = checkSequence(jobsSeq, dec_a.empV, newPen, feasible);
+        if (!res) return std::nullopt;
+
+        // Construire le voisin
+        SASolution neighbor = sol;
+        unsigned int newCost = 0;
+        applySequenceResult(neighbor, jobsSeq, *res, newCost, newPen, feasible);
+
+        neighbor.penalty          = sol.penalty - oldPen + newPen;
+        neighbor.penaltyPerMachine[dec_a.empV] = newPen;
+        neighbor.isFeasible       = neighbor.penalty.isFeasible();
+        neighbor.fictiveCost      = (neighbor.fictiveCost - oldCost) + newCost;
         neighbor.cost             = (neighbor.cost        - oldCost) + newCost;
         neighbor.source           = ESourceTrackPlan::SimAn;
         return neighbor;
-        };
-
-        //TEST SWAP
-        std::uniform_int_distribution<int> posR(0, (int)seq_swap.size()-1);
-        auto job = posR(randomEngine);
-        auto IposA = std::distance(seq_swap.begin(), posA);
-        while(job == IposA)
-            job = posR(randomEngine);
-
-        auto seqCop = seq_swap;
-        auto posJobInt = job;
-        seqCop[posJobInt] = *posA;
-        seqCop[IposA] = seq_swap[job];
-        auto res = lbdBuildSeq(seqCop);
-        if(res != std::nullopt)
-            return res;
-
-        return std::nullopt;
     }
 
     std::optional<SASolution> SimulatedAnnealing::move_swap_WC(const SASolution& sol)
@@ -397,6 +402,12 @@ namespace solverlib {
         auto oldCrenA = dec_a.lastCreneau;
         auto oldCrenB = dec_b.lastCreneau;
         
+        // Pénalités anciennes O(1)
+        Penalty oldPenA = sol.penaltyPerMachine.count(dec_a.empV)
+            ? sol.penaltyPerMachine.at(dec_a.empV) : Penalty{};
+        Penalty oldPenB = sol.penaltyPerMachine.count(dec_b.empV)
+            ? sol.penaltyPerMachine.at(dec_b.empV) : Penalty{};
+
         std::vector<std::pair<unsigned short, decision>> jobsEmpVA;
         std::vector<std::pair<unsigned short, decision>> jobsEmpVB;
         unsigned int oldCost = dec_a.lastCreneau.first * STFMockInstance::jobs[op_a]->getPoidsRetard() + dec_b.lastCreneau.first * STFMockInstance::jobs[swap.op_b]->getPoidsRetard();
@@ -443,30 +454,22 @@ namespace solverlib {
             }
             return cren1.first < cren2.first;
         });
-        auto resA = checkSequence(jobsEmpVA, new_dec_a.empV);
+
-        auto resB = checkSequence(jobsEmpVB, new_dec_b.empV);
+        Penalty penA; Penalty penB;
+        bool feasA = true, feasB = true;
+        auto resA = checkSequence(jobsEmpVA, new_dec_a.empV, penA, feasA);
+        auto resB = checkSequence(jobsEmpVB, new_dec_b.empV, penB, feasB);
         unsigned int newCost = 0;
-        if(resA && resB)
+        if(!resA || !resB) return std::nullopt;
-        {
+
-            unsigned int id = 0;
+        applySequenceResult(neighbor, jobsEmpVA, *resA, newCost, penA, feasA);
-            for(auto& jobsA : jobsEmpVA)
+        applySequenceResult(neighbor, jobsEmpVB, *resB, newCost, penB, feasB);
-            {
+
-                auto& dec = neighbor.decisions[jobsA.first];
+        neighbor.penalty                    = sol.penalty - oldPenA - oldPenB + penA + penB;
-                dec.lastCreneau = resA.value()[id].second.lastCreneau;
+        neighbor.penaltyPerMachine[new_dec_a.empV] = penA;
-                newCost += dec.lastCreneau.first * STFMockInstance::jobs[jobsA.first]->getPoidsRetard();
+        neighbor.penaltyPerMachine[new_dec_b.empV] = penB;
-                ++id;
+        neighbor.isFeasible                 = neighbor.penalty.isFeasible();
-            }
+        neighbor.fictiveCost                = (neighbor.fictiveCost - oldCost) + newCost;
-            id = 0;
-            for(auto& jobsB : jobsEmpVB)
-            {
-                auto& dec = neighbor.decisions[jobsB.first];
-                dec.lastCreneau = resB.value()[id].second.lastCreneau;
-                newCost += dec.lastCreneau.first * STFMockInstance::jobs[jobsB.first]->getPoidsRetard();
-                ++id;
-            }
-        }
-        else
-            return std::nullopt;
         neighbor.cost                       = (neighbor.cost        - oldCost) + newCost;
         neighbor.source                     = ESourceTrackPlan::SimAn;
         return neighbor;
@@ -517,8 +520,12 @@ namespace solverlib {
         new_dec_a.timeslotGraphSplited = mock->trajectoryStops[new_dec_a.empR].getDispoStop();
         new_dec_a.lastCreneau = {0,0};
         
-        unsigned int oldCost = MAXIMUM_TIME_OFFSET*STFMockInstance::jobs[op_a]->getPoidsRetard();
+        // Pénalité ancienne O(1) — séquence sans op_a
+        Penalty oldPen = sol.penaltyPerMachine.count(new_dec_a.empV)
+            ? sol.penaltyPerMachine.at(new_dec_a.empV) : Penalty{};
+
         unsigned int oldDiagCost = 0;
+        unsigned int oldCostScheduled = 0;
         unsigned int newDiagCost = new_dec_a.rejected ? STFMockInstance::jobs[op_a]->getPoidsRejet() : 0;
         std::vector<std::pair<unsigned short, decision>> jobsEmpVA;
         for(auto& dec : neighbor.decisions)
@@ -528,7 +535,7 @@ namespace solverlib {
                 if(dec.second.empV == new_dec_a.empV)
                 {
                     jobsEmpVA.push_back({dec.first, dec.second});
-                    oldCost += dec.second.lastCreneau.first * STFMockInstance::jobs[dec.first]->getPoidsRetard();
+                    oldCostScheduled += dec.second.lastCreneau.first * STFMockInstance::jobs[dec.first]->getPoidsRetard();
                 }
             }
         }
@@ -550,25 +557,31 @@ namespace solverlib {
         else {
             seq.insert(seq.begin() + pos, std::make_pair(op_a, new_dec_a));
         }
-        unsigned int newCost = 0;
-        auto res = checkSequence(seq, new_dec_a.empV);
-        if(res)
-        {
-            unsigned int id = 0;
-            for(auto& jobsA : seq)
-            {
-                auto& dec = neighbor.decisions[jobsA.first];
-                dec.lastCreneau = res.value()[id].second.lastCreneau;
-                newCost += dec.lastCreneau.first * STFMockInstance::jobs[jobsA.first]->getPoidsRetard();
-                ++id;
-            }
-            neighbor.diagCost = (neighbor.diagCost - oldDiagCost) + newDiagCost;
-            neighbor.cost = (neighbor.cost - oldCost) + newCost;
-            neighbor.source = ESourceTrackPlan::SimAn;
-            return neighbor;
-        }
         
-        return std::nullopt;
+        unsigned int newCost = 0;
+        Penalty penA; bool feasA = true;
+        auto res = checkSequence(seq, new_dec_a.empV, penA, feasA);
+        
+        if(!res) return std::nullopt;
+
+        applySequenceResult(neighbor, seq, *res, newCost, penA, feasA);
+
+        double oldFictive = sol.fictiveExcludedCosts.count(op_a)
+            ? fictiveCostExcluded(op_a)
+            : MAXIMUM_TIME_OFFSET * STFMockInstance::jobs[op_a]->getPoidsRetard();
+
+        unsigned int oldCostExcluded = MAXIMUM_TIME_OFFSET * STFMockInstance::jobs[op_a]->getPoidsRetard();
+
+        neighbor.penalty                       = sol.penalty - oldPen + penA;
+        neighbor.penaltyPerMachine[new_dec_a.empV] = penA;
+        neighbor.isFeasible                    = neighbor.penalty.isFeasible();
+        neighbor.fictiveCost                   = (neighbor.fictiveCost - oldFictive - oldCostScheduled) + newCost;
+        neighbor.fictiveExcludedCosts.erase(op_a);
+        neighbor.diagCost                      = (neighbor.diagCost - oldDiagCost) + newDiagCost;
+        neighbor.cost                          = (neighbor.cost - oldCostExcluded - oldCostScheduled) + newCost;
+        neighbor.source                        = ESourceTrackPlan::SimAn;
+
+        return neighbor;        
     }
 
     std::optional<SASolution> SimulatedAnnealing::move_move_WC(const SASolution& sol)
@@ -619,6 +632,12 @@ namespace solverlib {
         new_dec_a.timeslotGraphSplited = mock->trajectoryStops[new_dec_a.empR].getDispoStop();
         new_dec_a.lastCreneau = {0,0};
         
+        // Pénalités anciennes O(1) — machine de départ et machine d'arrivée
+        Penalty oldPenSrc = sol.penaltyPerMachine.count(dec_a.empV)
+            ? sol.penaltyPerMachine.at(dec_a.empV) : Penalty{};
+        Penalty oldPenDst = sol.penaltyPerMachine.count(new_dec_a.empV)
+            ? sol.penaltyPerMachine.at(new_dec_a.empV) : Penalty{};
+
         unsigned int oldCost = dec_a.lastCreneau.first*STFMockInstance::jobs[op_a]->getPoidsRetard();
         unsigned int oldDiagCost = dec_a.rejected ? STFMockInstance::jobs[op_a]->getPoidsRejet() : 0;
         unsigned int newDiagCost = new_dec_a.rejected ? STFMockInstance::jobs[op_a]->getPoidsRejet() : 0;
@@ -658,18 +677,15 @@ namespace solverlib {
         });
 
         unsigned int newCost = 0;
+        Penalty penA; Penalty penB;
+        bool feasA = true; bool feasB = true;
         //décale à gauche sur track de départ
-        auto resB = checkSequence(jobsEmpVB, dec_a.empV);
+        if(!jobsEmpVB.empty())
-        unsigned int id = 0;
-        for(auto& jobsB : jobsEmpVB)
         {
-            auto& dec = neighbor.decisions[jobsB.first];
+            auto resB = checkSequence(jobsEmpVB, dec_a.empV, penB, feasB);
-            dec.lastCreneau = resB.value()[id].second.lastCreneau;
+            applySequenceResult(neighbor, jobsEmpVB, *resB, newCost, penB, feasB);
-            newCost+= dec.lastCreneau.first * STFMockInstance::jobs[jobsB.first]->getPoidsRetard();
-            ++id;
         }
 
-
         std::uniform_int_distribution<unsigned int> distPos(0,jobsEmpVA.size());
         auto pos = distPos(randomEngine);
         
@@ -681,26 +697,22 @@ namespace solverlib {
         else {
             seq.insert(seq.begin() + pos, std::make_pair(op_a, new_dec_a));
         }
-        auto res = checkSequence(seq, new_dec_a.empV);
+        auto res = checkSequence(seq, new_dec_a.empV, penA, feasA);
-        if(res)
+        if(!res) return std::nullopt;
-        {
+    
-            unsigned int id = 0;
+        applySequenceResult(neighbor, seq, *res, newCost, penA, feasA);
-            for(auto& jobsA : seq)
+
-            {
+        neighbor.penalty                        = sol.penalty - oldPenSrc - oldPenDst + penB + penA;
-                auto& dec = neighbor.decisions[jobsA.first];
+        neighbor.penaltyPerMachine[dec_a.empV]  = penB;
-                dec.lastCreneau = res.value()[id].second.lastCreneau;
+        neighbor.penaltyPerMachine[new_dec_a.empV] = penA;
-                newCost+= dec.lastCreneau.first * STFMockInstance::jobs[jobsA.first]->getPoidsRetard();
+        neighbor.isFeasible                     = neighbor.penalty.isFeasible();
-                ++id;
+        neighbor.fictiveCost                    = (neighbor.fictiveCost - oldCost) + newCost;
-            }
         neighbor.diagCost                       = (neighbor.diagCost - oldDiagCost) + newDiagCost;
         neighbor.cost                           = (neighbor.cost      - oldCost) + newCost;
         neighbor.source                         = ESourceTrackPlan::SimAn;
         return neighbor;
     }
 
-        return std::nullopt;
-    }
-
     std::optional<SASolution> SimulatedAnnealing::move_remove_WC(const SASolution& sol)
     {
         auto mock = sol.mock;
@@ -729,9 +741,12 @@ namespace solverlib {
         new_dec_a.timeslotGraphSplited = CreneauHoraire();
         new_dec_a.lastCreneau = {0,0};
         
+        // Pénalité ancienne O(1) — inclut la contribution de op_a
+        Penalty oldPen = sol.penaltyPerMachine.count(dec_a.empV)
+            ? sol.penaltyPerMachine.at(dec_a.empV) : Penalty{};
+
         unsigned int oldCost = dec_a.lastCreneau.first * STFMockInstance::jobs[op_a]->getPoidsRetard();
         unsigned int oldDiagCost = dec_a.rejected ? STFMockInstance::jobs[op_a]->getPoidsRejet() : 0;
-        unsigned int newDiagCost = 0;
 
         std::vector<std::pair<unsigned short, decision>> jobsEmpVA;
         for(auto& dec : neighbor.decisions)
@@ -745,33 +760,32 @@ namespace solverlib {
                 }
             }
         }
-        unsigned int newCost = MAXIMUM_TIME_OFFSET * STFMockInstance::jobs[op_a]->getPoidsRetard();
 
+        unsigned int remaining = 0.0;
+        Penalty penA; bool feasA = true; 
         if(!jobsEmpVA.empty())
         {
-
             std::sort(jobsEmpVA.begin(), jobsEmpVA.end(), [&](auto& el1, auto& el2){
                 auto cren1 = el1.second.lastCreneau;
                 auto cren2 = el2.second.lastCreneau;
                 return cren1.first < cren2.first;
             });
-            auto resA = checkSequence(jobsEmpVA, dec_a.empV);
+            auto resA = checkSequence(jobsEmpVA, dec_a.empV, penA, feasA);
-            if(resA)
+            if(!resA) return std::nullopt;
-            {
+            
-                unsigned int id = 0;
+            applySequenceResult(neighbor, jobsEmpVA, *resA, remaining, penA, feasA);
-                for(auto& jobsA : jobsEmpVA)
-                {
-                    auto& dec = neighbor.decisions[jobsA.first];
-                    dec.lastCreneau = resA.value()[id].second.lastCreneau;
-                    newCost += dec.lastCreneau.first * STFMockInstance::jobs[jobsA.first]->getPoidsRetard();
-                    ++id;
         }
-            }
+
-            else
+        double fictivePenalty = fictiveCostExcluded(op_a);
-                return std::nullopt;
+        unsigned int excludedCost = MAXIMUM_TIME_OFFSET * STFMockInstance::jobs[op_a]->getPoidsRetard();
-        }
+
-        neighbor.diagCost = (neighbor.diagCost - oldDiagCost) + newDiagCost;
+        neighbor.penalty                       = sol.penalty - oldPen + penA;
-        neighbor.cost = (neighbor.cost - oldCost) + newCost;
+        neighbor.penaltyPerMachine[dec_a.empV] = penA;
+        neighbor.isFeasible                    = neighbor.penalty.isFeasible();
+        neighbor.fictiveExcludedCosts[op_a]    = fictivePenalty;
+        neighbor.fictiveCost                   = (neighbor.fictiveCost - oldCost) + fictivePenalty + remaining;
+        neighbor.diagCost                      = neighbor.diagCost - oldDiagCost;
+        neighbor.cost                          = (neighbor.cost - oldCost) + excludedCost + remaining;
         neighbor.source                        = ESourceTrackPlan::SimAn;
         return neighbor;
     }
@@ -793,9 +807,9 @@ namespace solverlib {
         SASolution neighbor = sol;
         Decision& new_dec_a = neighbor.decisions[op_a];
 
+        
         unsigned int oldDiagCost = dec_a.rejected ? STFMockInstance::jobs[op_a]->getPoidsRejet() : 0;
         unsigned int newDiagCost = dec_a.rejected ? 0 : STFMockInstance::jobs[op_a]->getPoidsRejet();
-        unsigned int oldCost = 0;
         if(dec_a.rejected)
         {
             new_dec_a.rejected = false;
@@ -810,6 +824,11 @@ namespace solverlib {
             }
         }
         
+        // Pénalité ancienne O(1)
+        Penalty oldPen = sol.penaltyPerMachine.count(dec_a.empV)
+        ? sol.penaltyPerMachine.at(dec_a.empV) : Penalty{};
+        
+        unsigned int oldCost = 0;
         std::vector<std::pair<unsigned short, decision>> jobsEmpVA;
         for(auto& dec : neighbor.decisions)
         {
@@ -829,23 +848,17 @@ namespace solverlib {
             return cren1.first < cren2.first;
         });
         unsigned int newCost = 0;
-        if(!jobsEmpVA.empty())
+
-        {
+        Penalty penA; bool feasA = true;
-            auto resA = checkSequence(jobsEmpVA, dec_a.empV);
+        auto resA = checkSequence(jobsEmpVA, dec_a.empV, penA, feasA);
-            if(resA)
+        if(!resA) return std::nullopt;
-            {
+        
-                unsigned int id = 0;
+        applySequenceResult(neighbor, jobsEmpVA, *resA, newCost, penA, feasA);
-                for(auto& jobsA : jobsEmpVA)
+    
-                {
+        neighbor.penalty                       = sol.penalty - oldPen + penA;
-                    auto& dec = neighbor.decisions[jobsA.first];
+        neighbor.penaltyPerMachine[dec_a.empV] = penA;
-                    dec.lastCreneau = resA.value()[id].second.lastCreneau;
+        neighbor.isFeasible                    = neighbor.penalty.isFeasible();
-                    newCost += dec.lastCreneau.first * STFMockInstance::jobs[jobsA.first]->getPoidsRetard();
+        neighbor.fictiveCost                   = (neighbor.fictiveCost - oldCost) + newCost;
-                    ++id;
-                }
-            }
-            else
-                return std::nullopt;
-        }
         neighbor.diagCost                      = (neighbor.diagCost - oldDiagCost) + newDiagCost;
         neighbor.cost                          = (neighbor.cost      - oldCost) + newCost;
         neighbor.source                        = ESourceTrackPlan::SimAn;
@@ -872,53 +885,53 @@ namespace solverlib {
         return std::optional<std::vector<std::pair<unsigned short, Decision>>>(res);
     }
 
-
+    std::optional<std::vector<std::pair<unsigned short, Decision>>>
-    std::pair<bool, std::vector<unsigned int>> SimulatedAnnealing::PSE_Carlier_Rivreau(std::vector<std::pair<unsigned short, decision>> &jobs, unsigned int voieMachine) {
+    SimulatedAnnealing::checkSequence(
-
+        const std::vector<std::pair<unsigned short, Decision>>& jobsDec,
-        std::stringstream fakeFile;
+        unsigned int machine,
-
+        Penalty& outPenalty, 
-        for (unsigned int i = 0; i < jobs.size(); ++i) {
+        bool&   outFeasible)
-            auto match = CreneauHoraire::checkSlotsCompatibility(jobs[i].second.timeslotGraphSplited,
-                                                                    STFMockInstance::machines[voieMachine]->getDispo());
-            fakeFile << i + 1;
-            fakeFile << " " << match.second.first;
-            if (!jobs[i].second.rejected) {
-                fakeFile << " " << STFMockInstance::jobs[jobs[i].first]->getDuree();
-            } else
-                fakeFile << " " << STFMockInstance::jobs[jobs[i].first]->getDureeDiag();
-            fakeFile << " " << match.second.first + match.second.second;
-            fakeFile << std::endl;
-        }
-        std::ifstream file;
-        file.basic_ios<char>::rdbuf(fakeFile.rdbuf());
-        Solution sol((int) jobs.size());
-        OneMachine machine(file);
-        machine.solve(sol);
-
-        std::vector<unsigned int> solution(jobs.size());
-        for (unsigned int i = 0; i < jobs.size(); ++i) {
-            solution[i] = sol.startTime[i+1];
-        }
-
-        return {machine.checkSol(sol) && sol.Lmax <= 0, solution};
-    }
-
-
-    /*unsigned long SimulatedAnnealing::getUniquePlans(std::vector<TrackPlan>& plans)
     {
-        std::set<TrackPlan> uniqueSchedules;
+        auto machineDisp = STFMockInstance::machines[machine]->getDispo();
-        std::vector<TrackPlan> newTMPVec;
+        unsigned short minBegin = machineDisp.getDebut().getRelativeDate();
-        for(auto& trackSch : plans)
+        std::vector<std::pair<unsigned short, Decision>> res;
+        outFeasible = true;
+
+        for (auto& jobDec : jobsDec)
         {
-            uniqueSchedules.insert(trackSch);
+            auto matchWithMachine = CreneauHoraire::checkSlotsCompatibility(
+                jobDec.second.timeslotGraphSplited, machineDisp).second;
+
+            minBegin = std::max(minBegin, matchWithMachine.first);
+            unsigned int duration = !jobDec.second.rejected
+                ? STFMockInstance::jobs[jobDec.first]->getDuree()
+                : STFMockInstance::jobs[jobDec.first]->getDureeDiag();
+
+            unsigned int windowEnd = matchWithMachine.first + matchWithMachine.second;
+            unsigned int jobEnd    = minBegin + duration;
+
+            if (jobEnd > windowEnd)
+            {
+                if (!authorizeInfeasible)
+                    return std::nullopt;
+
+                // Planification forcée + pénalité
+                outFeasible = false;
+                double overrun   = static_cast<double>(jobEnd - windowEnd);
+                outPenalty.add(EPenaltyType::TIME_WINDOW_OVERRUN, overrun);
             }
-        auto uniqueNb = uniqueSchedules.size();
-        std::move(uniqueSchedules.begin(), uniqueSchedules.end(), std::back_inserter(newTMPVec));
-        std::swap(plans, newTMPVec);
-
-        return uniqueNb;
-    }*/
-
-
 
+            auto newJobDec = jobDec;
+            newJobDec.second.lastCreneau = {minBegin, jobEnd};
+            minBegin = jobEnd;
+            res.push_back(newJobDec);
+        }
+        for (size_t i = 1; i < res.size(); ++i) {
+            if (res[i].second.lastCreneau.first < res[i-1].second.lastCreneau.second && res[i].second.lastCreneau.first >= res[i-1].second.lastCreneau.first) {
+                std::cout << res[i].second.lastCreneau.first << " " << res[i].second.lastCreneau.second << " " << res[i-1].second.lastCreneau.first << " " << res[i-1].second.lastCreneau.second << std::endl;
+                throw std::logic_error("Chevauchement détecté");
+            }
+        }
+        return res;
+    }    
 }

src/OrdoCorr/Solver/TrackPlansILP/SimulatedAnnealing.hpp

@@ -6,16 +6,17 @@
 #include <random>
 #include <unordered_map>
 #include <vector>
+#include "Penalty.hpp"
 #include "TrackPlan.hpp"
 #include "Solution.hpp"
 namespace solverlib {
     using namespace modellib;
 
     enum class EMovingOperators{
-        SWAP_WITHOUT_CARLIER,
+        SWAP,
-        INSERT_WITHOUT_CARLIER,
+        INSERT,
-        REMOVE_WITHOUT_CARLIER,
+        REMOVE,
-        CHANGE_MODE_WITHOUT_CARLIER,
+        CHANGE_MODE,
         SWAP_WITHIN_INTERVAL,
         MOVE,
         DYN_PROG,
@@ -24,13 +25,18 @@ namespace solverlib {
     struct StatSimulatedAnnealing{
         struct failInf{
             double prob;
-            unsigned int diff;
+            long diff;
+            double fictiveDiff;
             double temperature;
+            bool isfeasible = true;
         };
 
         std::unordered_map<EMovingOperators, unsigned int> nbUsed;
         std::unordered_map<EMovingOperators, unsigned int> nbFeas; 
         std::unordered_map<EMovingOperators, unsigned int> nbImproved; 
+        std::unordered_map<EMovingOperators, unsigned int> nbImprovedReal; 
+        std::unordered_map<EMovingOperators, unsigned int> nbInfeasible; 
+
         std::unordered_map<EMovingOperators, std::vector<failInf>> failInfos; 
 
 
@@ -48,10 +54,17 @@ namespace solverlib {
         void addImproved(EMovingOperators op){
             if(activate) nbImproved[op]++;
         }
+        void addImprovedReal(EMovingOperators op){
+            if(activate) nbImprovedReal[op]++;
+        }
 
-        void addFailInfo(EMovingOperators op, double prob, unsigned int diff, double temp)
+        void addInfeasible(EMovingOperators op){
+            if(activate) nbInfeasible[op]++;
+        }
+
+        void addFailInfo(EMovingOperators op, double prob, long diff, double fictiveDiff, double temp, bool isFeasible)
         {
-            if(activate) failInfos[op].emplace_back(failInf{prob, diff, temp});
+            if(activate) failInfos[op].emplace_back(failInf{prob, diff, fictiveDiff, temp});
         }
     };
 
@@ -59,12 +72,47 @@ namespace solverlib {
         private:
             std::vector<SASolution> solutions;
             std::mt19937 randomEngine;
+            double T;
+            double Tmax;
+            double Tmin;
+            double maxCostOfJob;
+            double rate;
+
+            void applySequenceResult(
+                SASolution& neighbor,
+                const std::vector<std::pair<unsigned short, Decision>>& seq,
+                const std::vector<std::pair<unsigned short, Decision>>& resolved,
+                unsigned int& newCost,
+                Penalty penaltyDelta,    // pénalité de cette séquence
+                bool feasible)
+            {
+                unsigned int id = 0;
+                for (auto& job : seq)
+                {
+                    auto& dec = neighbor.decisions[job.first];
+                    dec.lastCreneau = resolved[id].second.lastCreneau;
+                    newCost += dec.lastCreneau.first * STFMockInstance::jobs[job.first]->getPoidsRetard();
+                    ++id;
+                }
+                neighbor.penalty = neighbor.penalty + penaltyDelta;
+                if (!feasible) neighbor.isFeasible = false;
+            }
+
+            std::unordered_map<EPenaltyType, double> penaltyLambdas;
+
+            // Initialisation dans le constructeur ou avant solve()
+            void setPenaltyWeights() {
+                penaltyLambdas[EPenaltyType::TIME_WINDOW_OVERRUN] = 1.0;
+            }
+            std::unordered_map<EPenaltyType, double> effectiveLambdas() const;
+
         public:
             static bool withDynProg;
+            static bool authorizeInfeasible;
             StatSimulatedAnnealing stats;
             SimulatedAnnealing() = delete;
             explicit SimulatedAnnealing(std::unordered_map<unsigned short, Decision>& decs, std::shared_ptr<modellib::STFMockInstance> mock, ESourceTrackPlan source);
-            EMovingOperators pick_operator(double tmax, double t);
+            EMovingOperators pick_operator();
             std::optional<SASolution> apply_operator(const SASolution& current, EMovingOperators op);
             SASolution solve(double T_max, double T_min, double cooling_rate, int iterations_per_temp);
 
@@ -77,15 +125,17 @@ namespace solverlib {
             std::optional<SASolution> move_dynprog(const SASolution& sol);
 
             std::optional<std::vector<std::pair<unsigned short, Decision>>> checkSequence(const std::vector<std::pair<unsigned short, Decision>>& jobsDec, unsigned int machine);
+            std::optional<std::vector<std::pair<unsigned short, Decision>>> checkSequence(const std::vector<std::pair<unsigned short, Decision>>& jobsDec, unsigned int machine, Penalty& outPenalty, bool& outFeasible);
 
-            double getP(double delta, double temperature, EMovingOperators op);
+            double getP(double delta, EMovingOperators op);
+            double effectiveCost(const SASolution& s) const;
+
+            double progress() const;
+
+            double fictiveCostExcluded(unsigned short op_id) const;
 
             std::pair<unsigned int, unsigned int> evaluate(const std::unordered_map<unsigned short, Decision>& decs);
 
-            std::pair<unsigned int, unsigned int> getCostOfSequence(std::vector<std::pair<unsigned short, decision>>& jobsSeq);
-
-            std::pair<bool, std::vector<unsigned int>> PSE_Carlier_Rivreau(std::vector<std::pair<unsigned short, decision>> &jobs, unsigned int voieMachine);
-
             void addSolutions(std::vector<SASolution>& solPool){solutions.insert(solutions.end(), solPool.begin(), solPool.end());};
 
 

src/OrdoCorr/Solver/TrackPlansILP/Solution.hpp

@@ -2,6 +2,7 @@
 #define SOLUTION_HPP
 
 #include "../../../General/Model/STFMockInstance.hpp"
+#include "Penalty.hpp"
 #include "sourceSolTrPlan.hpp"
 
 namespace solverlib {
@@ -13,6 +14,11 @@ namespace solverlib {
         std::unordered_map<unsigned short, Decision> decisions;
         unsigned int       cost;     
         unsigned int       diagCost;    
+        bool isFeasible = true;
+        Penalty penalty;
+        std::unordered_map<unsigned int, Penalty> penaltyPerMachine;
+        double fictiveCost = 0.0;
+        std::unordered_map<unsigned short, double> fictiveExcludedCosts;
     }SASolution;
 }
 

src/OrdoCorr/Solver/TrackPlansILP/SolutionPoolManager.cpp

@@ -1,5 +1,7 @@
 #include "SolutionPoolManager.hpp"
 #include <iterator>
+#include <unordered_map>
+#include <vector>
 
 namespace solverlib {
     std::vector<TrackPlan> SolutionPoolManager::getTrackPlansFromSolution(SASolution& sol, bool withTrash)
@@ -10,14 +12,17 @@ namespace solverlib {
         //id plan = id voie
         std::vector<TrackPlan> plans;
         plans.resize(STFMockInstance::tracks.size());
+        std::unordered_map<unsigned int, std::vector<std::pair<unsigned short, Decision>>> decisionsOnMachines;
+        std::vector<std::set<unsigned int>> machineIdsFromTrackId(STFMockInstance::tracks.size());
         for(auto& dec : sol.decisions)
         {
             if(!dec.second.excluded)
             {
-                plans[dec.second.voie].source = sol.source;
                 plans[dec.second.voie].isTrash = false;
                 plans[dec.second.voie].track = dec.second.voie;
                 plans[dec.second.voie].schedule[dec.first] = dec.second;
+                decisionsOnMachines[dec.second.empV].push_back({dec.first, dec.second});
+                machineIdsFromTrackId[dec.second.voie].insert(dec.second.empV);
             }
             else if(withTrash) {
                 TrackPlan trashTrack;
@@ -36,6 +41,23 @@ namespace solverlib {
         for(auto& plan : plans)
         {
             if(!plan.schedule.empty())
+            {
+
+                bool feasible = true;
+                if(!sol.penalty.isFeasible())
+                {
+                    for(auto& machine : machineIdsFromTrackId[plan.track])
+                    {
+                        std::sort(decisionsOnMachines[machine].begin(), decisionsOnMachines[machine].end(), [&](auto& el, auto& el2){
+                            return el.second.lastCreneau.first < el2.second.lastCreneau.first;
+                        });
+                        feasible = checkSequence(decisionsOnMachines[machine], plan.track);
+                        if(!feasible)
+                            break;
+                    }
+                    
+                }
+                if(feasible)
                 {
                     plan.mock = sol.mock;
                     plan.source = sol.source;
@@ -43,6 +65,7 @@ namespace solverlib {
                     trackPlans.push_back(plan);
                 }
             }
+        }
 
         return trackPlans;
     }
@@ -56,11 +79,13 @@ namespace solverlib {
         trackPlans.reserve(STFMockInstance::tracks.size() * pool.size() + 1);
         while(!pool.empty())
         {
-            auto& sol = pool.back();
+            auto sol = pool.back();
 
             //id plan = id voie
             std::vector<TrackPlan> plans;
             plans.resize(STFMockInstance::tracks.size());
+            std::unordered_map<unsigned int, std::vector<std::pair<unsigned short, Decision>>> decisionsOnMachines;
+            std::vector<std::set<unsigned int>> machineIdsFromTrackId(STFMockInstance::tracks.size());
             for(auto& dec : sol.decisions)
             {
                 if(!dec.second.excluded)
@@ -68,11 +93,30 @@ namespace solverlib {
                     plans[dec.second.voie].isTrash = false;
                     plans[dec.second.voie].track = dec.second.voie;
                     plans[dec.second.voie].schedule[dec.first] = dec.second;
+                    decisionsOnMachines[dec.second.empV].push_back({dec.first, dec.second});
+                    machineIdsFromTrackId[dec.second.voie].insert(dec.second.empV);
+
                 }
             }
             for(auto& plan : plans)
             {
                 if(!plan.schedule.empty())
+                {
+                    bool feasible = true;
+                    if(!sol.penalty.isFeasible())
+                    {
+                        for(auto& machine : machineIdsFromTrackId[plan.track])
+                        {
+                            std::sort(decisionsOnMachines[machine].begin(), decisionsOnMachines[machine].end(), [&](auto& el, auto& el2){
+                                return el.second.lastCreneau.first < el2.second.lastCreneau.first;
+                            });
+                            feasible = checkSequence(decisionsOnMachines[machine], plan.track);
+                            if(!feasible)
+                                break;
+                        }
+                        
+                    }
+                    if(feasible)
                     {
                         plan.mock = sol.mock;
                         plan.source = sol.source;
@@ -83,7 +127,12 @@ namespace solverlib {
                             countD++;
                         }
                     }
+                    else {
+                        countD++;
                     }
+                }
+            }
+
             pool.pop_back();
         }
         std::move(uniqueSchedules.begin(), uniqueSchedules.end(), std::back_inserter(trackPlans));       
@@ -104,12 +153,31 @@ namespace solverlib {
 
         auto nbplan = trackPlans.size();
 
-        loggerlib::Logger::systemNotify(loggerlib::LOGGER_PROGRESS, "Removed " + std::to_string(countD) + " non-unique track schedules");
+        loggerlib::Logger::systemNotify(loggerlib::LOGGER_PROGRESS, "Removed " + std::to_string(countD) + " non-unique or non-feasible track schedules");
         loggerlib::Logger::systemNotify(loggerlib::LOGGER_PROGRESS, "Total track plans " + std::to_string(nbplan));
 
         return trackPlans;
     }
 
+    bool SolutionPoolManager::checkSequence(const std::vector<std::pair<unsigned short, Decision>>& jobsDec, unsigned int machine)
+    {
+        auto machineDisp = STFMockInstance::machines[machine]->getDispo();
+        unsigned short minBegin = machineDisp.getDebut().getRelativeDate();
+        std::vector<std::pair<unsigned short, Decision>> res;
+        for(auto& jobDec : jobsDec)
+        {
+            auto matchWithMachine = CreneauHoraire::checkSlotsCompatibility(jobDec.second.timeslotGraphSplited, machineDisp).second;
+            minBegin = std::max(minBegin, matchWithMachine.first);
+            auto newJobDec = jobDec;
+            unsigned int duration = !jobDec.second.rejected ? STFMockInstance::jobs[jobDec.first]->getDuree() : STFMockInstance::jobs[jobDec.first]->getDureeDiag();
+            newJobDec.second.lastCreneau = {minBegin, minBegin + duration};
+            if(minBegin + duration > matchWithMachine.first + matchWithMachine.second)
+                return false;
+            minBegin = minBegin + duration;
+        }
+        return true;
+    }
+
     void SolutionPoolManager::provide(std::vector<SASolution>&& solutions)
     {
         std::move(solutions.begin(), solutions.end(), std::back_inserter(pool));

src/OrdoCorr/Solver/TrackPlansILP/SolutionPoolManager.hpp

@@ -16,6 +16,8 @@ namespace solverlib {
 
             std::vector<TrackPlan> getTrackPlansFromSolution(SASolution& sol, bool withTrash = false);
 
+            bool checkSequence(const std::vector<std::pair<unsigned short, Decision>>& jobsDec, unsigned int machine);
+
             const std::vector<SASolution>& getSolutions() const {return pool;};
     };
 

src/OrdoCorr/Solver/solverAPI.cpp

@@ -853,14 +853,14 @@ namespace solverlib {
                 std::ostringstream csv;
 
                 // En-têtes
-                csv << "category;operator;index;probability;objectiveDiff;temperature \n";
+                csv << "category;operator;index;probability;objectiveDiff;costDiff;temperature;isFeasible\n";
 
                 // worseProb (map de vector)
                 for(auto& [key, val] : simAnn.stats.failInfos)
                 {
                     for(size_t i = 0; i < val.size(); ++i)
                     {
-                        csv << ";" << simAnn.stats.names[key] << ";" << i << ";" << val[i].prob << ";" << val[i].diff << ";" << val[i].temperature << "\n";
+                        csv << ";" << simAnn.stats.names[key] << ";" << i << ";" << val[i].prob << ";" << val[i].diff << ";" << val[i].fictiveDiff << ";" << val[i].temperature << ";" << val[i].isfeasible << "\n";
                     }
                 }
 
@@ -869,11 +869,16 @@ namespace solverlib {
                 for(auto& [map, label] : std::vector<std::pair<std::unordered_map<EMovingOperators, unsigned int>, std::string>>{
                         {simAnn.stats.nbUsed,     "used"},
                         {simAnn.stats.nbFeas,     "feas"},
-                        {simAnn.stats.nbImproved, "improved"}})
+                        {simAnn.stats.nbImproved, "improved"},
+                        {simAnn.stats.nbImprovedReal, "improvedRealCost"},
+                        {simAnn.stats.nbInfeasible, "withPenalty"}
+
+                    })
                 {
                     for(auto& [key, val] : map)
                     {
                         if(label == "used") nbIte += val;
+
                         csv << label << ";" << simAnn.stats.names[key] << ";" << ";" << val << "\n";
                     }
                 }
@@ -939,7 +944,7 @@ namespace solverlib {
         std::vector<PipelineConfig> pipelines = {
 
             //{{ALGO::LH, ALGO::DYNPROG }, false, false},
-            {{ALGO::LH, ALGO::SIMANN}, false, false},
+            {{ALGO::LH, ALGO::SIMANN, ALGO::ILP}, false, false, 7},
 
             /*{{ALGO::LH, ALGO::SIMANN, ALGO::ILP}, false, false},
             {{ALGO::LH, ALGO::SIMANN, ALGO::ILP}, false, false, 1},
@@ -994,7 +999,10 @@ namespace solverlib {
                                 if(i > 0)
                                 {
                                     std::uniform_int_distribution<unsigned int> distSol(0, poolManager.getSolutions().size()-1);
+                                    do{
                                         sol = poolManager.getSolutions()[distSol(rng)];
+
+                                    }while(!sol.penalty.isFeasible());
                                 }
                                 auto res = runSimAnn(sol, poolManager, false);
                                 result.stepsRes.push_back(res);
@@ -1049,6 +1057,11 @@ namespace solverlib {
                         }
                     }
                 }
+                SASolution sol = result.best.sol;
+                SolutionPoolManager sp;
+                sp.provide({sol});
+                auto res = runILP(sol, sp);
+
                 double timeFinal = 0.0;
                 nlohmann::json arrStep = nlohmann::json::array();
                 for(auto& stepFinished : result.stepsRes)