Genetic Algorithm for Vehicle Routing Problem with Backhauls

Abstract

The Vehicle Routing Problem with Backhauls (VRPB) is an extension of the classical Vehicle Routing Problem (VRP) that includes both a set of customers to whom products are to be delivered and a set of suppliers whose goods need to be transported back to the distribution center. In addition, on each route all deliveries have to be made before any goods can be picked up to avoid rearranging the loads on the vehicle. The main objective for VRPB is to determine the network route to minimize the total cost, distance or time. There are a few methods that can be identified to solve this VRPB. The objective of this research is to present a heuristic method, called Genetic Algorithm (GA), for the VRPB. In brief, GA is a system developing methods that use the natural principle of a genetic population and involved three main processes that is crossover, mutation and inversion. GA implementation on the 68 nodes problems taken from Goetschalckx and Jacobs- Blecha is done by using Microsoft C++ Programming. Solutions to the problem are presented and performance comparison is conducted with the existing best solution. Several parameters in GA will be tested such as population size, crossover point and also the choice of operators used.