Systematic Diversification Metaheuristic for the Vehicle Routing Problem with Time Windows

This paper introduces an extension of the multi-start local search framework [1, 2, 3], named Systematic Diversification for the Vehicle Routing Problem with Time Windows, where the objective is to design least cost routes for a fleet of vehicles from one depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval; all routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. The problem has been under intensive research during the past few years because of its high practical importance. The suggested method is based on systematically penalizing solution features/attributes to diversify the search within a multi-start local search, where the basic idea is to create several initial solutions, and apply improvement heuristics to each of them. Then, the best solution found during the search is the final output. The experimental results on the well-known 100-customer benchmarks show that the described approach is reliable, effective and robust, being very competitive with all previous methods found in the literature.