A Fast Evolutionary Metaheuristic for the Vehicle Routing Problem with Time Windows

Abstract

This paper presents a new evolutionary metaheuristic for the vehicle routing problem with time windows. Ideas on multi-start local search, ejection chains, simulated annealing and evolutionary computation are combined in a heuristic that is both robust and efficient. The proposed method produces results that are on par with the current best solutions, at a fraction of the computation time needed by previous best approaches. Given the significantly lower time consumption over methods proposed previously in the literature, we consider our approach especially useful in dynamic routing problems, where decisions must be made in real-time.