Research On Optimization Of Transportation Cost In Logistics Enterprises With Time Constraints

With the development of science and technology, it becomes more difficult to increase the enterprises’profit through the improvement of product performance and labor productivity. In a competitive environment, it is crucial for the success of an enterprise about how to obtain the maximum profit. Note that, logistics cost occupies a large portion of the total cost of enterprises, and it can be reduced through a part of supply chain optimization. In order to gain advantage in the increasingly competitive commodity market, the enterprises are committed to the study on the logistics optimization. Through the analysis of the logistics cost in the logistics enterprises, we find that the transportation cost constitutes a high proportion of the logistics enterprises’cost. Therefore, it is very important that the optimization of transportation cost in the logistics enterprises is studied. It has the theoretical and realistic significance from the long term.The transportation cost of logistics enterprises is influenced by the fixed cost and the variable cost during the transportation process. It is more related to the customers’ time window constraints for the transportation time. The logistics enterprises pay the penalty according to the time window constraints specified by the customers, and then it causes the increase in the transportation cost. The time windows can be categorized into three headings:the soft time windows, the hard time windows and the mixed time windows. Because the soft time windows are common in real transportation, our main concern is soft time windows. Considering the influence of the traffic and human factor, the vehicle transportation is often interrupted which causes the transportation time extension. This phenomenon is called time-switch constraints which are not considered by recent literatures. By ignoring the impact of the time-switch constraints in the logistics enterprises, it results in transportation time prediction error made by the logistics enterprises’decision makers. Therefore, the research on the transportation cost model with time-switch constraints could better reflect the actual transportation process.It is noted that the difficult point and the shortcoming of existing models related to transportation cost with time window constraints have shown in the literatures. This paper firstly analyzes the classification of time windows, and then determines the application scope of different time windows. Furthermore, this paper puts the time-switch constraints of the project network into the transportation problem by using the project network to express the vehicle routing. Most importantly, this paper introduces the time-switch constraints into the established transportation cost model with the time windows constraints. Through the analysis of these two models, we notice that the impact of the time-switch constraints in the logistics enterprises can not be ignored. In the process of modeling, the vehicle number of the logistics enterprises being as the important factor influences the transportation cost. Therefore, the model has two objectives:the minimization of the transportation cost and the minimization of the total number of vehicle in the logistics enterprises. For solving this model, an improved genetic algorithm is developed. At last, an example of a process of S logistics enterprise demonstrates its capabilities.Based on the above studies, this paper makes a future research in relation to transportation cost in the logistics enterprises caused by time-switch constraints. By means of real-world test application, we find out two phenomena. Firstly, the actual transportation cost influenced by time-switch constraints is higher than that calculated by the classical transportation cost model. What’s more, the time-switch constraints make the optimal transportation path in the logistics enterprises a change. In particular, the impact of the time-switch constraints on logistics enterprises is shown in this paper.