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fixup
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‎cmake/docker/web/Dockerfile‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -4,7 +4,7 @@ FROM archlinux:latest AS env
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55
# Install system build dependencies
66
ENV PATH=/usr/local/bin:$PATH
7-
RUN pacman -Syu --noconfirm git base-devel glibc cmake
7+
RUN pacman -Syu --noconfirm git base-devel cmake
88
RUN cmake -version
99
RUN pacman -Syu --noconfirm nodejs emscripten
1010
ENV PATH=/usr/lib/emscripten:$PATH

‎ortools/routing/csharp/routing.i‎

Lines changed: 0 additions & 27 deletions
Original file line numberDiff line numberDiff line change
@@ -129,33 +129,6 @@ using System.Collections.Generic;
129129
using Google.OrTools.ConstraintSolver;
130130
using Domain = Google.OrTools.Util.Domain;
131131
%}
132-
%typemap(cscode) RoutingDimension %{
133-
// Keep reference to delegate to avoid GC to collect them early.
134-
private List<IntIntToLong> limitCallbacks;
135-
private IntIntToLong StoreIntIntToLong(IntIntToLong limit) {
136-
if (limitCallbacks == null)
137-
limitCallbacks = new List<IntIntToLong>();
138-
limitCallbacks.Add(limit);
139-
return limit;
140-
}
141-
142-
private List<LongLongToLong> groupDelayCallbacks;
143-
private LongLongToLong StoreLongLongToLong(LongLongToLong groupDelay) {
144-
if (groupDelayCallbacks == null)
145-
groupDelayCallbacks = new List<LongLongToLong>();
146-
groupDelayCallbacks.Add(groupDelay);
147-
return groupDelay;
148-
}
149-
%}
150-
%ignore RoutingDimension::GetBreakDistanceDurationOfVehicle;
151-
152-
// RoutingModel
153-
%unignore RoutingModel;
154-
%typemap(csimports) RoutingModel %{
155-
using System;
156-
using System.Collections.Generic;
157-
using Domain = Google.OrTools.Util.Domain;
158-
%}
159132
%typemap(cscode) RoutingModel %{
160133
// Keep reference to delegate to avoid GC to collect them early.
161134
private List<LongToLong> unaryTransitCallbacks;

‎ortools/routing/java/routing.i‎

Lines changed: 0 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -71,12 +71,6 @@ namespace operations_research::routing {
7171
import com.google.ortools.constraintsolver.Constraint;
7272
%}
7373

74-
// GlobalVehicleBreaksConstraint
75-
%typemap(javaimports) GlobalVehicleBreaksConstraint %{
76-
// Types from ConstraintSolver
77-
import com.google.ortools.constraintsolver.Constraint;
78-
%}
79-
8074
// RoutingModel
8175
%unignore RoutingModel;
8276
// Map transit callback to Java @FunctionalInterface types.

‎ortools/routing/search.cc‎

Lines changed: 0 additions & 183 deletions
Original file line numberDiff line numberDiff line change
@@ -261,189 +261,6 @@ const Assignment* SolveFromAssignmentWithAlternativeSolversAndParameters(
261261
return best_assignment;
262262
}
263263

264-
namespace {
265-
void ConvertAssignment(const RoutingModel* src_model, const Assignment* src,
266-
const RoutingModel* dst_model, Assignment* dst) {
267-
DCHECK_EQ(src_model->Nexts().size(), dst_model->Nexts().size());
268-
DCHECK_NE(src, nullptr);
269-
DCHECK_EQ(src_model->solver(), src->solver());
270-
DCHECK_EQ(dst_model->solver(), dst->solver());
271-
for (int i = 0; i < src_model->Nexts().size(); i++) {
272-
IntVar* const dst_next_var = dst_model->NextVar(i);
273-
if (!dst->Contains(dst_next_var)) {
274-
dst->Add(dst_next_var);
275-
}
276-
dst->SetValue(dst_next_var, src->Value(src_model->NextVar(i)));
277-
}
278-
}
279-
280-
bool AreAssignmentsEquivalent(const RoutingModel& model,
281-
const Assignment& assignment1,
282-
const Assignment& assignment2) {
283-
for (IntVar* next_var : model.Nexts()) {
284-
if (assignment1.Value(next_var) != assignment2.Value(next_var)) {
285-
return false;
286-
}
287-
}
288-
return true;
289-
}
290-
291-
absl::Duration GetTimeLimit(const RoutingSearchParameters& search_parameters) {
292-
return search_parameters.has_time_limit()
293-
? util_time::DecodeGoogleApiProto(search_parameters.time_limit())
294-
.value()
295-
: absl::InfiniteDuration();
296-
}
297-
298-
// TODO(user): Refactor this function with other versions living in
299-
// routing.cc.
300-
// TODO(user): Should we update solution limits as well?
301-
bool UpdateTimeLimits(Solver* solver, int64_t start_time_ms,
302-
absl::Duration time_limit,
303-
RoutingSearchParameters& search_parameters) {
304-
if (!search_parameters.has_time_limit()) return true;
305-
const absl::Duration elapsed_time =
306-
absl::Milliseconds(solver->wall_time() - start_time_ms);
307-
const absl::Duration time_left =
308-
std::min(time_limit - elapsed_time, GetTimeLimit(search_parameters));
309-
if (time_left <= absl::ZeroDuration()) return false;
310-
const absl::Status status = util_time::EncodeGoogleApiProto(
311-
time_left, search_parameters.mutable_time_limit());
312-
DCHECK_OK(status);
313-
return true;
314-
}
315-
} // namespace
316-
317-
const Assignment* SolveWithAlternativeSolvers(
318-
RoutingModel* primary_model,
319-
const std::vector<RoutingModel*>& alternative_models,
320-
const RoutingSearchParameters& parameters,
321-
int max_non_improving_iterations) {
322-
return SolveFromAssignmentWithAlternativeSolvers(
323-
/*assignment=*/nullptr, primary_model, alternative_models, parameters,
324-
max_non_improving_iterations);
325-
}
326-
327-
const Assignment* SolveFromAssignmentWithAlternativeSolvers(
328-
const Assignment* assignment, RoutingModel* primary_model,
329-
const std::vector<RoutingModel*>& alternative_models,
330-
const RoutingSearchParameters& parameters,
331-
int max_non_improving_iterations) {
332-
return SolveFromAssignmentWithAlternativeSolversAndParameters(
333-
assignment, primary_model, parameters, alternative_models, {},
334-
max_non_improving_iterations);
335-
}
336-
337-
const Assignment* SolveFromAssignmentWithAlternativeSolversAndParameters(
338-
const Assignment* assignment, RoutingModel* primary_model,
339-
const RoutingSearchParameters& primary_parameters,
340-
const std::vector<RoutingModel*>& alternative_models,
341-
const std::vector<RoutingSearchParameters>& alternative_parameters,
342-
int max_non_improving_iterations) {
343-
const int64_t start_time_ms = primary_model->solver()->wall_time();
344-
if (max_non_improving_iterations < 0) return nullptr;
345-
// Shortcut if no alternative models will be explored.
346-
if (max_non_improving_iterations == 0 || alternative_models.empty()) {
347-
return primary_model->SolveFromAssignmentWithParameters(assignment,
348-
primary_parameters);
349-
}
350-
RoutingSearchParameters mutable_search_parameters = primary_parameters;
351-
// The first alternating phases are limited to greedy descent. The final pass
352-
// at the end of this function will actually use the metaheuristic if needed.
353-
// TODO(user): Add support for multiple metaheuristics.
354-
const LocalSearchMetaheuristic_Value metaheuristic =
355-
mutable_search_parameters.local_search_metaheuristic();
356-
const bool run_metaheuristic_phase =
357-
metaheuristic != LocalSearchMetaheuristic::GREEDY_DESCENT &&
358-
metaheuristic != LocalSearchMetaheuristic::AUTOMATIC;
359-
if (run_metaheuristic_phase) {
360-
mutable_search_parameters.set_local_search_metaheuristic(
361-
LocalSearchMetaheuristic::GREEDY_DESCENT);
362-
}
363-
std::vector<RoutingSearchParameters> mutable_alternative_parameters =
364-
alternative_parameters;
365-
DCHECK(mutable_alternative_parameters.empty() ||
366-
mutable_alternative_parameters.size() == alternative_models.size());
367-
for (RoutingSearchParameters& mutable_alternative_parameter :
368-
mutable_alternative_parameters) {
369-
if (!mutable_alternative_parameter.has_time_limit() &&
370-
mutable_search_parameters.has_time_limit()) {
371-
*mutable_alternative_parameter.mutable_time_limit() =
372-
mutable_search_parameters.time_limit();
373-
}
374-
}
375-
const absl::Duration time_limit = GetTimeLimit(mutable_search_parameters);
376-
Assignment* best_assignment = primary_model->solver()->MakeAssignment();
377-
std::vector<Assignment*> first_solutions;
378-
first_solutions.reserve(alternative_models.size());
379-
for (RoutingModel* model : alternative_models) {
380-
first_solutions.push_back(model->solver()->MakeAssignment());
381-
}
382-
Assignment* primary_first_solution =
383-
primary_model->solver()->MakeAssignment();
384-
Assignment* current_solution = primary_model->solver()->MakeAssignment();
385-
DCHECK(assignment == nullptr ||
386-
assignment->solver() == primary_model->solver());
387-
const Assignment* solution = primary_model->SolveFromAssignmentWithParameters(
388-
assignment, mutable_search_parameters);
389-
if (solution == nullptr) return nullptr;
390-
best_assignment->Copy(solution);
391-
int iteration = 0;
392-
while (iteration < max_non_improving_iterations) {
393-
if (best_assignment->ObjectiveValue() > solution->ObjectiveValue()) {
394-
best_assignment->Copy(solution);
395-
}
396-
current_solution->Copy(solution);
397-
for (int i = 0; i < alternative_models.size(); ++i) {
398-
RoutingSearchParameters& mutable_alternative_parameter =
399-
mutable_alternative_parameters.empty()
400-
? mutable_search_parameters
401-
: mutable_alternative_parameters[i];
402-
if (!UpdateTimeLimits(primary_model->solver(), start_time_ms, time_limit,
403-
mutable_alternative_parameter)) {
404-
return best_assignment;
405-
}
406-
ConvertAssignment(primary_model, solution, alternative_models[i],
407-
first_solutions[i]);
408-
solution = alternative_models[i]->SolveFromAssignmentWithParameters(
409-
first_solutions[i], mutable_alternative_parameter);
410-
if (solution == nullptr) {
411-
solution = first_solutions[i];
412-
}
413-
if (!UpdateTimeLimits(primary_model->solver(), start_time_ms, time_limit,
414-
mutable_search_parameters)) {
415-
return best_assignment;
416-
}
417-
ConvertAssignment(alternative_models[i], solution, primary_model,
418-
primary_first_solution);
419-
solution = primary_model->SolveFromAssignmentWithParameters(
420-
primary_first_solution, mutable_search_parameters);
421-
if (solution == nullptr) return best_assignment;
422-
}
423-
// No modifications done in this iteration, no need to continue.
424-
if (AreAssignmentsEquivalent(*primary_model, *solution,
425-
*current_solution)) {
426-
break;
427-
}
428-
// We're back to the best assignment which means we will cycle if we
429-
// continue the search.
430-
if (AreAssignmentsEquivalent(*primary_model, *solution, *best_assignment)) {
431-
break;
432-
}
433-
if (solution->ObjectiveValue() >= best_assignment->ObjectiveValue()) {
434-
++iteration;
435-
}
436-
}
437-
if (run_metaheuristic_phase &&
438-
UpdateTimeLimits(primary_model->solver(), start_time_ms, time_limit,
439-
mutable_search_parameters)) {
440-
mutable_search_parameters.set_local_search_metaheuristic(metaheuristic);
441-
return primary_model->SolveFromAssignmentWithParameters(
442-
best_assignment, mutable_search_parameters);
443-
}
444-
return best_assignment;
445-
}
446-
447264
// --- VehicleTypeCurator ---
448265

449266
void VehicleTypeCurator::Reset(const std::function<bool(int)>& store_vehicle) {

‎ortools/routing/search.h‎

Lines changed: 0 additions & 42 deletions
Original file line numberDiff line numberDiff line change
@@ -48,48 +48,6 @@
4848

4949
namespace operations_research::routing {
5050

51-
// Solves a routing model using alternative models. This assumes that the models
52-
// are equivalent in the sense that a solution to one model is also a solution
53-
// to the other models. This is true for models that differ only by their arc
54-
// costs or objective for instance.
55-
// The primary model is the main model, to which the returned solution will
56-
// correspond.
57-
// The method solves the primary model and alternative models alternatively.
58-
// It works as follows (all solves use 'parameters'):
59-
// 1) solve the primary model with a greedy descent,
60-
// 2) let 'alt' be the first alternative model,
61-
// 3) solve 'alt' starting from the solution to the primary model with a greedy
62-
// descent,
63-
// 4) solve the primary model from the solution to 'alt' with a greedy descent,
64-
// 5) if the new solution improves the best solution found so far, update it,
65-
// otherwise increase the iteration counter,
66-
// 6) if the iteration counter is less than 'max_non_improving_iterations', let
67-
// 'alt' be the next "round-robin" alternative model, and go to step 3,
68-
// 7) if 'parameters' specified a metaheuristic, solve the primary model using
69-
// that metaheuristic starting from the best solution found so far,
70-
// 8) return the best solution found.
71-
// Note that if the time limit is reached at any stage, the search is
72-
// interrupted and the best solution found will be returned immediately.
73-
// TODO(user): Add a version taking search parameters for alternative models.
74-
const Assignment* SolveWithAlternativeSolvers(
75-
RoutingModel* primary_model,
76-
const std::vector<RoutingModel*>& alternative_models,
77-
const RoutingSearchParameters& parameters,
78-
int max_non_improving_iterations);
79-
// Same as above, but taking an initial solution.
80-
const Assignment* SolveFromAssignmentWithAlternativeSolvers(
81-
const Assignment* assignment, RoutingModel* primary_model,
82-
const std::vector<RoutingModel*>& alternative_models,
83-
const RoutingSearchParameters& parameters,
84-
int max_non_improving_iterations);
85-
// Same as above but taking alternative parameters for each alternative model.
86-
const Assignment* SolveFromAssignmentWithAlternativeSolversAndParameters(
87-
const Assignment* assignment, RoutingModel* primary_model,
88-
const RoutingSearchParameters& parameters,
89-
const std::vector<RoutingModel*>& alternative_models,
90-
const std::vector<RoutingSearchParameters>& alternative_parameters,
91-
int max_non_improving_iterations);
92-
9351
// Solves a routing model using alternative models. This assumes that the models
9452
// are equivalent in the sense that a solution to one model is also a solution
9553
// to the other models. This is true for models that differ only by their arc

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