The Impact of Crossover and Mutation Operators on a GA Solution for the Capacitated Vehicle Routing Problem

摘要

The Vehicle Routing Problem (VRP) is one of the well-known NP hard problems requiring excessive time to be exactly solved. Therefore, for solving this type of problems, some researchers implemented meta-heuristics such as Genetic Algorithm (GA). In this paper, we study the Capacitated VRP (CVRP) which has some constraints on the capacities of the vehicles used in VRP. The goal of this study is to observe the impact of the selected operators of GA on the quality of the generated solutions. Therefore, we propose 6 different GAs by mixing and combining 3 crossover and 5 mutation operators. We observed the performance of these solutions by applying them over 10 CVRP benchmarks.