Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4636814 | Applied Mathematics and Computation | 2006 | 17 Pages |
Much of the research on operations scheduling problems has either ignored setup times or assumed that setup times on each machine are independent of the job sequence. This paper deals with the hybrid flow shop scheduling problems in which there are sequence dependent setup times, commonly known as the SDST hybrid flow shops. This type of production system is found in industries such as chemical, textile, metallurgical, printed circuit board, and automobile manufacture. With the increase in manufacturing complexity, conventional scheduling techniques for generating a reasonable manufacturing schedule have become ineffective. An immune algorithm (IA) can be used to tackle complex problems and produce a reasonable manufacturing schedule within an acceptable time. This paper describes an immune algorithm approach to the scheduling of a SDST hybrid flow shop. An overview of the hybrid flow shops and the basic notions of an IA are first presented. Subsequently, the details of an IA approach are described and implemented. The results obtained are compared with those computed by Random Key Genetic Algorithm (RKGA) presented previously. From the results, it was established that IA outperformed RKGA.