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Update pickup_vrp API to be in par with the rest of the library #108
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This method optimize_model() can be reused in pickup_vrp LP solvers, where we need to iterate over it without retrieving directly GPDPDSolution (which forget about some necessary attributes in the loop).
- Iterative solving of using Mip library has some strange behaviour, leading to unfeasible problems. - This commit permits to circumvent the issue by reinitializing the TSP linear model at each iteration of the algo - To keep in memory subtour elimination constraints, we store the necessary info in pure python object (list_constraints_tuple), the constraint can be reintroduced from a clean model. - This patch is not very efficient when the LP is large to initialize.
It was specific to usecase, not tested, and deprecated.
as discussed, this PR is satisfactory and we identified some things to code further (better satisfy function for gpdp problem) |
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solve()
does return aResultStorage
.What this PR does not solve:
LinearFlowSolverVehicleType
are unfinished