A new hybrid algorithm for solving the vehicle routing problem with route balancing

This paper addresses a vehicle routing problem with route balancing to minimize the to-tal travel cost and equity measurement. We propose a hybrid method combining Particle Swarm Optimization and Ant Colony Optimization with the global search characteristic of PSO and the path-finding ability of ACO. The proposed method first solves the benchmark instances to obtain the total travel distance and the equity measurement value. Then, by considering predefined threshold values of the equity measurement in the original solution, the vehicle routing problem with route balancing can be solved using the proposed method. Experiments are conducted to obtain better-balanced routes by considering more than one equity measurement. The results showed that this hybrid mechanism is promising to become a better method of VRP.