The Multiple-Objective Scheduling in Flow Shop Scheduling with Sequence Dependent Setup Times

• Main Authors: Shihkai Lin, 林士凱
• Other Authors: none
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/23029911661643003808

碩士 === 國立雲林科技大學 === 工業工程與管理研究所碩士班 === 91 === Due to the changing market and the short life span of the products, the production system becomes to complex problem. It is the important that the business needs to catch up with market trend to get more profit and responds to customer needs quickly by a efficiently scheduling system. XX plastic company developed the PP plastic synthetic paper that to reduce the woods chopped. The PP plastic synthetic paper involves three different production stages, the fist is coating engineering, the second is rewinding engineering, the finally is package engineering. The production system is a typically flow shop. In traditional seller’s market, scheduling focus on high-volume, low-cost and high-utilization production by planning. Now, in buyer’s market, scheduling focus on how to satisfy the demands of customer. Because flow shop scheduling problems have been proved as NP-hard problems to simplify the studies, the majority of scheduling research assumes setup and removal as negligible or part of the processing time. With the changing of production type, taking setup time into consideration is getting more and more important for actual industrial schedulers. In practice, the setup time depends on sequence of works. This paper is to develop a improving genetic algorithm (GA) to solve flow shop scheduling with sequence dependent setup time. In this study, the multiple-objective of GA is to get maximal total amount profit due to the loss of delay and early and minimize makespan to increase machine running time to get the profit. We use the Taguchi experiments model of two stage to get the best parameters, population size, crossover type, crossover rate, mutation rate, generation number and initial solution type, etc. The performance of the GA is compared with the traditional dispatching rule,NEH,EDD and actual schedule rule of company. All the results show that the GA of this paper is superior to the other approaches.