Order-oriented Job Shop And Logistics Vehicle Joint Scheduling

With the rapid development of social economy and the diversification of material products,the buyer’s market oriented by customer demand has become the dominant market economy,and enterprises have changed their production system from inventory production to order production.On the other hand,in the previous study of the production-distribution joint scheduling problem,many scholars have done a lot of research on the strategic and tactical level.Modern supply chain management is a refined operation,so the study on the specific operation level is more and more important.In the production environment,most scholars study the joint scheduling under the environment of single machine and parallel machine,and the production mode of complex production environment,such as job shop scheduling and flow shop scheduling,is still rare.Therefore,Under the order production mode,this paper studies the joint scheduling problem of workshop and logistics vehicles,and extends the scheduling link to the procurement of raw materials,mainly including the following aspects:(1)The order-oriented joint scheduling model of workshop and logistics vehicles is established.Aiming at different scheduling tasks of raw material procurement,process processing and finished product distribution,a mathematical model was constructed with the objective of minimizing scheduling time under certain assumptions,and the NP property of the problem was proved.The scheduling method adopted in this paper was explained by a simple test case step by step.(2)An artificial swarm algorithm using role reversal is used.Firstly,the characteristics of the joint scheduling problem and algorithm are analyzed.Second,the weight of each task scheduling is represented by the coding method of two-dimensional matrix.In order to make the initial value of the matrix differentiated,a transformation function was designed to convert the random number between(0,1)to(0,1)real number initial value.Finally,the heuristic information is embedded in the process of decoding to make the solution more extensive and to make the solution better.(3)Through a large number of test cases and comparative experiments,it is shown that the combined scheduling strategy in this paper is more effective,and compared with other algorithms,the artificial bee colony algorithm designed in thispaper is better to obtain the optimal solution.