Optimizing Single Depot Heterogeneous Fleet Vehicle Routing Problem by Improved Genetic Algorithm

Abstract

Firstly, the paper establishes a mathematical model for single depot and heterogeneous fleet vehicle routing problem (SHVRP) according to the actual situation of Zhengzhou Coal Electricity Material Supply and Marketing Limited Company in China, then based on the model, uses improved genetic algorithm(IGA) to optimize the vehicle routing problem (VRP) of Zhengzhou Coal Electricity Material Supply and Marketing Limited Company, finally by comparing the performance of IGA with classical heuristics algorithm (CHA) and sweeping algorithm(SA) in transportation cost, the number of used vehicle and computing time, the results show that CHA obtains the best objective function value, SA takes the second place, and CHA is the poorest; however, from the number of used vehicles, the optimum solution of CHA uses the least vehicles, followed by SA and IGA; but CHA is most efficient on computing time, the time needed for calculation is only two fifth of that of SA, two twenty five of that of IGA.