Tabu search techniques for the heterogeneous vehicle routing problem with time windows and carrier-dependent costs
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In this work we formalize a new complex variant of the classical vehicle routing problem arising from a real-world application. Our formulation includes a heterogeneous fleet, a multi-day planning horizon, a complex carrier-dependent cost for vehicles, and the possibility of leaving orders unscheduled.
For tackling this problem we propose a metaheuristic approach based on Tabu Search and on a combination of neighborhood relations. We perform an experimental analysis to tune and compare different combinations, highlighting the most important features of the algorithm.
The outcome is that a significant improvement is obtained by a complex combination of neighborhood relations.
In addition, we compare our solver with previous work on public benchmarks of a similar version of the problem, namely the Vehicle Routing Problem with Private fleet and Common carrier. The conclusion is that our results are competitive with the best ones in literature.
KeywordsVehicle routing Tabu search
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