Solving capacitated vehicle routing problem using chicken swarm optimization with genetic algorithm

Abstract

The Capacitated Vehicle Routing Problem is the most popular type of Vehicle Routing Problem and is a kind of NP-hard problems. Finding the minimum total distance travelled by vehicles to serve a group of customers with respect to capacity constrains is the aim of the Capacitated Vehicle Routing Problem. This problem will be solved by hybrid algorithm combining Chicken Swarm Optimization algorithm with Genetic Algorithm using Crossover and Mutation operation. The main idea of the proposed algorithm is to use the hieratical order of Chicken Swarm Algorithm to find paths after using the moving equations. Then we will rearrange the hieratical order according the paths cost. In an attempt to improve results for some chickens, we will use the Genetic Algorithm because it has the advantage that it searches in the neighbourhood to find the best solution then we will get the best solution which has the lowest cost. Results from a computational experiment on 10 different datasets show that the hybrid algorithm can be considered as an efficient approach and overcome the best known results in 10 datasets which means that it is 100% better than best known results which exist on NEO benchmark.