A multi-objective memetic algorithm for risk minimizing vehicle routing problem and scheduling problem

Abstract

In this paper, a new approach to risk minimizing vehicle routing and scheduling problem is presented. Forwarding agents or companies have two main concerns for the collection of high-risk commodities like cash or valuable commodities between the central depot and the customers: one; because of the high value of the commodities transported, the risk of ambush and robbery are very high. Two; the cost of a security guard that protects the vehicle is high. Therefore, the goals of these companies are to deliver and collect commodities with maximum security and minimum risk. Hence, in this paper, a multi-objective vehicle routing problem with time windows (VRPTW) is proposed to minimize risk and transportation costs. Finally, a memetic algorithm is designed to optimize the proposed model. The proposed algorithm is evaluated and compared with the non-dominated genetic algorithm (NSGAII) using Solomon VRPTW test sets. The results demonstrate that the presented approach is effective for valuables routing problem.