Coordination Scheduling Problem Of Single Machine Manufacturing With Delivery In Supply Chain Environment

Coordination has become the core concept of supply chain management. With the rapid development of the global economy, the coordination between the supply chain partners has become an important problem of supply chain management. It can help the enterprise reduce cost; improve the level of service; response to the market quickly, so becomes hot topic. This thesis focuses on the topic of coordination scheduling which covers manufacture and transportation in supply chain environment. The main contents are as follows:(1) In a 2-tier supply chain system composed of a manufacturer and multiple customers, the issue of coordinating production and delivery with constraints of making one batch for the same customer is studied. The main characteristics of this problem are as follows:to meet demands of different customers, various size jobs have been processed in the single machine environment, and then transported to customers respectively. The jobs that transported at one time are called one batch, which belong to one customer. The objective is to determine the job processing sequence in the plant, the delivery schedule and the batching so as to minimize the sum of job flow times. After analyzing the properties of the schedules, bi-level programming model is built and the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm are designed. At last, the results of the GA algorithm and PSO algorithm in different examples are presented.(2) In a 2-tier supply chain system composed of a manufacturer and multiple customers, the issue of coordinating production and delivery with constraints of making one batch for different customers is studied. The main characteristics of this problem are as follows:to meet demands of different customers, various size jobs have been processed in the single machine environment, and then transported to customers respectively. The jobs that transported at one time are called one batch, which belong to different customers. The objective is to determine the job processing sequence in the plant; the delivery schedule; the batching and transporting path so as to minimize the sum of job flow times. After analyzing the properties of the optimal schedules, mathematical model is built and several heuristic rules are embedded in the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm which are proposed separately. At last, the results of the GA algorithm and PSO algorithm in different examples are presented.