| Summary: | 碩士 === 國立中興大學 === 資訊科學研究所 === 92 === Scheduling is an important process widely used in manufacturing, production, management, computer science, and so on. Finding good schedules for given sets of jobs can thus help factory supervisors effectively control job flows and provide solutions for job sequencing. In simple flow shop problems, each machine operation center includes just one machine. If at least one machine center includes more than one machine, the scheduling problem becomes a flexible flow-shop problem. Scheduling jobs in flexible flow shops is considered an NP-hard problem. Recently, group scheduling has also been proposed and discussed. In the group scheduling, each job belongs to a specific group and all the jobs are processed group by group. A heuristic algorithm for solving flexible flow-shop problems of two machine centers is proposed by Sriskandarajah and Sethi in 1989.
In this thesis, we thus adopt and extend their approach to solve flexible flow-shop and group flexible flow-shop scheduling problems. We first propose two methods to solve flexible flow-shop problems with more than two machine centers. The first method deals with a medium number of jobs to get a nearly minimum completion time by combining LPT and dynamic-programming. The second method deals with a large number of jobs to get a nearly minimum completion time by combining LPT and PT. We then propose two methods to solve group flexible flow-shop problems with two machine centers. The first method deals with a small number of jobs to get a minimum completion time by using dynamic-programming. The second method deals with a large number of jobs to get a nearly minimum completion time by combining LPT and Johnson. Furthermore, we also propose several methods to solve group flexible flow-shop problems with more than two machine centers.
At last, experiments are made to show the execution times and makespans of the proposed algorithms. The experimental results are totally consistent with our expectation. The choice among these proposed approaches to solve a specific flexible flow-shop problem thus depends on the problem size, the allowed execution time and the allowed error. A trade-off can thus be achieved between accuracy and time complexity.
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