Research On The4PL Routing Optimization Problem Based On Goal Programming

With the rapid development of global economy, trading between enterprises grows remarkably. At the same time, enterprises require that supply chain integration capabilities for logistics companies increases gradually. And they are eager to have a logistics company that has strong comprehensive strength to provide solutions for the whole supply chain and meet distribution services at the same time. In this demand environment, the fourth party logistics (4PL) appear, the appearance of which improves the operation efficiency and reduces the logistics transportation costs in a large part. So, research related it has great significance.The fourth party logistics role is mainly that organizing and using their mastery of the third party logistics supplier’s information optimize logistics supply chain, in which routing optimization is a key problem. Since the expectation of the enterprises is not just single goal in the real logistics transport problem, it needs to consider multiple goals which have priority and weight. Based on it, this paper investigates routing optimization problem of the fourth party logistics and applications about it at home or abroad and further considers the fourth party logistics routing optimization problem with multiple goals that have priority and weight.The research work of this paper is as follows. Through reviewing literature related the fourth party logistics, routing problem, the goal programming problem and differential evolution algorithm, this paper firstly establishs the mathematical model for single-point to single-point and single-task routing optimization problem of4PL. According to the differential evolution algorithm and the characteristics of problem, improved differential evolution algorithm is given and compared with genetic algorithm (GA). The result of comparisons shows that these algorithms can respectively solve the problem in different scale, and the former one has better solutions. Moreover, combined with multiple graph, the model for single-point to multi-point single-task routing optimization problem of4PL is proposed and also used improved differential evolution algorithm and Genetic algorithm to solve it. Through the comparison of the two algorithm and the parameter analysis, the result shows that the operations time of the improved differential evolution algorithm is very short and deviation is very small. So, improved differential evolution algorithm has good efficiency for the problem in this paper. In this paper, according to the expectation value that enterprises require and based on goal programming the result of research is helpful to the reality of logistics operation.