Solving a multi-objective vehicle scheduling-routing of interurban transportation fleet with the purpose of minimizing delays by Using the Differential Evolutionary Algorithm

Over the past three decades, the unified approach of the optimization of the logistic systems has become one of the most important aspects of optimizing the supply chain so that in recent decades it has had a large application in practice and has been used to increase the efficiency and effectiveness of the logistic fleet. The inter-urban transport networks by the terminals play an important role in logistic fleet and the goods distribution. In some cases, numbers of terminals face with an overload and others encounter with additional vehicles, which result delay in the load post and unnecessary car downtime. The present paper aims at modeling, scheduling and routing of the vehicles network and minimizing delays in order to create an optimal balance between the number of vehicles and the capacity of the car terminals to use the maximal capacity of vehicles. So that the multi-objective mathematical model is presented to quantify the regular transportation costs and to minimize the car downtime. The proposed model has two conflicting objectives where on tried to increase costs and the other decreases unused cars. Due to the high complexity of the problem, the multi-objective differential evolutionary algorithm (MODE) has been used. To prove the proposed algorithm, it has compared with the NSGA-II algorithm using four comparing indexes. The computational results show the superiority of the proposed algorithm.