Comments (8)
I'm not sure. What problem are you solving? A distance matrix alone is just data, and not something to optimise.
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I assume you mean the TSP example? Then it's a definite yes. You would have to change the evaluation of the objective (in State.objective()
) to sum the cost matrix c
over the edges (i, j)
between shops i
and j
that make up your solution.
Something like return sum(self.c[i, j] for i, j in self.edges)
, or the like should do!
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Related issue: #15.
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@suleman-81 I'm closing this issue because I have not heard from you for some time. If you something new to discuss, feel free to let me know by opening a new issue. Have a great day!
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The TSP example has been updated to do more or less exactly this now, resulting in a slight performance improvement as well.
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Related Issues (20)
- Integrate with MABWiser library HOT 2
- Integration with optimization modeling/solver software HOT 8
- Some quetions for using ALNS HOT 5
- Adaptive simulated annealing temperature and step-size HOT 4
- what's your alns.weights HOT 1
- Update docs
- Tasklist for next release HOT 2
- About other VRP destroy and repair operators HOT 3
- Bug in `examples/resource_constrained_project_scheduling_problem.ipynb:random_insert`?
- Circle bin packing with ALNS HOT 21
- Run example notebooks in CI HOT 1
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- How to solve vehicle routing problem with multiple capacities? HOT 5
- Documentation improvements HOT 2
- RCPSP示例中的“instance = ProblemData.read_instance('data/j9041_6.sm')”的数据在哪里 HOT 1
- Where is the data for "instance = ProblemData.read_instance('data/j9041_6.sm')" in the RCPSP example HOT 3
- Run w/o MABwiser in the CI
- Rename RandomWalk and WorseAccept? HOT 2
- Replace `RandomState` with `Generator` HOT 2
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