Abstract
The objective of this paper is to consider the vehicle routing problem with time windows under two uncertainties: service and travel times. We introduce new resolution approaches for the robust problem and an efficient parallel procedure for the generation of all possible scenarios. The best robust solution of each scenario can be achieved by using a parallel adaptive large neighborhood search metaheuristic. Through our analysis, we expect to find the best compromise between the reduced running time and a best good solution, which leads to four distinct combinations of parallel/sequential approaches. The computational experiments are performed and tested on Solomon’s benchmark and large randomly generated instances. Furthermore, our results can be protected against delay in service time in a reasonable running time especially for large instances.
Highlights
We study the robust vehicle routing problem with time windows where travel times and service times are both the subject of uncertainty
As far as the adopted approach derives the best robust solution that responds to all uncertainties, it still suffer from lengthy computational times; partly because the generation of scenarios, as well as the research of the solution block are time-consuming
As an alternative to remedy this problem, we introduce a procedure for the thread parallelism in the Monte
Summary
A generic class called the metaheuristic is used to exploit the best capabilities to achieve better solutions to solve a wide range of problems, since the mechanism to avoid getting trapped in local minima is present In this regard, the literature covers a considerable number of metaheuristics conceived of to solve the VRPTW such as Simulated Annealing (SA) [14,15], Variable Neighborhood Search (VNS) [16,17], Ant Colony Optimization. Their method is based mainly on two cooperating classes of heuristics, namely tabu search and the evolutionary algorithms In this regard, Røpke (2009) [25] applied a parallel ALNS to the traveling salesman problem with pickup and delivery and the capacitated vehicle routing problem such that each worker thread obtains a copy of the current solution and performs destroy and repair operations on its local copy in order to produce the best global solution. A detailed computational and comparative study is given before the concluding remarks and perspectives
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