A New Competitive Approach on Multi-Objective Periodic Vehicle Routing Problem

This paper presents a novel multi-objective mathematical model of a periodic vehicle routing problem (pvrp) in a competitive situation for obtaining more sales. in such a situation, the reaching time to customers affects the sale amount; therefore, distributors intend to service customers earlier than other rivals for obtaining the maximum sale. moreover, a partial driver’s benefit is related to the amount of their sale; thus, the balance of goods based on the vehicles capacity is important. due to its complexity, it is so difficult to optimally solve this problem in a reasonable computational time. hence, two algorithms are proposed based on multi-objective particle swarm optimization (mopso) and nsgaii algorithm. a comparison of our results with three performance metrics confirms that the proposed mopso is an efficient algorithm for solving the competitive pvrp with a reasonable computational time.