Clustering-Based Crossover In An Evolutionary Algorithm For The Vehicle Routing Problem With Time Windows

This paper addresses the Vehicle Routing Problem with Time Windows (VRPTW). A crossover operator which uses the information gathered by a clustering procedure is described. In the proposed approach, a hierarchical clustering procedure is applied to the customers' spatial data. The crossover procedure creates a new solution by removing and reinserting customers, and uses the clusters to identify the most promising reinsertion locations. Thus, the proposed operator avoids exhaustive search. Computational experiments show the effectiveness of the proposed operator, that produces competitive solutions and improves the overall performance of the evolutionary algorithm when compared against an approach based on exhaustive search.