Research On Intelligent Scheduling System Of S Logistics Company

With the fast development of China's economy,the logistics distribution industry developed very fast as well.So,enhancing the ability of logistics management and reducing the cost of the transportation are becoming the most effective means to strengthen the competitiveness of the logistics enterprise.Since the vehicle scheduling problem are complicated and covers a large scope and be many influence factors,how to build a highly effective and intelligent vehicle scheduling system is becoming a big challenge for the logistics companies,to achieve the purpose of the transportation cost saving and the service quality improvement.With the background of the S logistics company,this paper first analyzed the issues of the logistics transportation in S company,it's include:(l)Manual scheduling the transportation tasks,each operator should handing lots of vehicles at the same time;(2)the volume of each branches are nonuniform,with high empty-run rate;(3)limited daily mileage for both vehicle and driver,low transit time for each day,and low resources utilization.Secondly,this paper lays emphasis on the research of how to resolve the vehicle and driver scheduling optimization issue in transportation process in S company.To meet the requirements of different business,we were focused on the three specific scenarios,include(1)without consideration the sense of the different vehicle models;(2)multiple models of vehicles were considered;(3)without consideration of the vehicle models but included the working hours of the driver.We were used the dynamic programming algorithm for three scenarios modeling,and uses the genetic algorithm to research and resolve the related issues.It the end,through the data simulation technology this paper compared both the optimized scheduling scheme and manual scheduling scheme,the result shows that the proposed algorithm reduced both the number of vehicles and drivers,decreased the mileage of transportation and cut the transportation costs,and also further verify the effectiveness of the algorithm.In the meantime,this algorithm has the certain versatilities for other transportation issues in different logistics companies,and also it's worth as a reference for the similar issues resolving for different logistic companies.