A parallel iterated tabu search heuristic for vehicle routing problems

This paper introduces a parallel iterated tabu search heuristic for solving four different routing problems: the classical vehicle routing problem (VRP), the periodic VRP, the multi‐depot VRP, and the site‐dependent VRP. In addition, it is applicable to the time‐window constrained variant of these problems. Using the iterated local search framework, the heuristic combines tabu search with a simple perturbation mechanism to ensure a broad exploration of the search space. We also describe a parallel implementation of the heuristic to take advantage of multiple‐core processors. Extensive computational results show that the proposed heuristic outperforms tabu search alone and is competitive with recent heuristics designed for each particular problem.