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

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.