The Vehicle Routing Problem with Time Windows (VRPTW) is an important problem in logistics, which is an extension of well known Vehicle Routing Problem (VRP), with a central depot. The Objective is to design an optimal set of routes for serving a number of customers without violating the customer’s time window constraints and vehicle capacity constraint. It has received considerable attention in recent years. This paper reviews the research on Evolutionary Algorithms for VRPTW. The main types of evolutionary algorithms for the VRPTW are Genetic Algorithms and Evolutionary Strategies which may also be described as Evolutionary metaheuristics to distinguish them from other metaheuristics. Along with these evolutionary metaheuristics, this paper reviews heuristic search methods that hybridize ideas of evolutionary algorithms with some other search technique, such as tabu search, guided local search, route construction heuristics, ejection chain approach, adaptive large neighborhood search, variable neighborhood search and hierarchal tournament selection. In addition to the basic features of each method, experimental results for the 56 benchmark problem with 100 customers of Solomon (1987) and Gehring and Homberger (1999) are presented and analyzed
