Research On Supply Chain Scheduling Problem With Learning Effect

During the Second World War, the research object was set up for the first time, and the time arrangement of the research work led to the establishment of the concept of ranking and further research. After nearly sixty years of development, the ranking theory has played an important role in the field of discrete optimization, the domestic research on the sort theory has gradually diversified. Among them, the supply chain scheduling can effectively solve the problem of the distribution of the actual production operations. This paper mainly studies the supply chain scheduling problem under two different conditions of the supply chain scheduling problem and a class of subcontract. The first chapter is the introduction of this paper, first introduces the origin of scheduling theory, and then introduces the domestic and foreign research situation, and finally make a brief introduction to the framework. The second chapter on the machine with learning effect multi client distribution supply chain scheduling problem are discussed, aimed at for a transport vehicles loaded with no more than two customers of the job under the scheduling problem. The objective function is minimizing the total flow time and minimizing the delay time, and to the two questions are given the corresponding dynamic programming algorithm. The third chapter will in a two echelon supply chain development has become a three level supply chain, discussed in the machine with learning effect and a transport vehicles loaded with a multiple clients the job under the three level supply chain scheduling problem, using dynamic programming algorithm is used to study the maximum flow time, total flow time and maximum delay three objective functions, each objective function are given the corresponding dynamic programming algorithm. In the fourth chapter, combined with the subcontract concept research, the goal is to find an integrated scheme for the production, transportation and subcontract the total cost minimum, aiming at the goal gives a heuristic algorithm. This makes the scheduling problem research provides an effective solution to the real production complex.