A Reactive Greedy Randomized Variable Neighborhood Tabu Search for the Vehicle Routing Problem with Time Windows

Abstract

This paper presents a hybrid metaheuristic to address the vehicle routing problem with time windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from a depot to geographically dispersed customers. The routes must be designed such that each customer is visited only once by exactly one vehicle without violating capacity and time window constraints. The proposed solution method is a multi-start local search approach which combines reactively the systematic diversification mechanisms of Greedy Randomized Adaptive Search Procedures with a novel Variable Neighborhood Tabu Search hybrid metaheuristic for intensification search. Experimental results on well known benchmark instances show that the suggested method is both efficient and robust in terms of the quality of the solutions produced.