Hybrid genetic algorithm for test bed scheduling problems
| Autor: | Soo-Heon Lee, Anh-Dung Do Ngoc, Ilkyeong Moon |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Engineering
Mathematical optimization test bed Job shop scheduling production scheduling business.industry Strategy and Management Scheduling (production processes) Dynamic priority scheduling Management Science and Operations Research Industrial and Manufacturing Engineering Fair-share scheduling Shipbuilding Integer programming model genetic algorithm business integer programming Integer programming |
| Zdroj: | Do, N A D, Lee, S H & Moon, I 2014, ' Hybrid genetic algorithm for test bed scheduling problems ', International Journal of Production Research, vol. 52, no. 4, pp. 1074-1089 . https://doi.org/10.1080/00207543.2013.838327 |
| ISSN: | 1366-588X 0020-7543 |
| DOI: | 10.1080/00207543.2013.838327 |
| Popis: | In this paper, we address the scheduling problem for a heavy industry company which provides ship engines for shipbuilding companies. Before being delivered to customers, ship engines are assembled, tested and disassembled on the test beds. Because of limited test bed facilities, it is impossible for the ship engine company to satisfy all customers orders. Therefore, they must select the orders that can be feasibly scheduled to maximise profit. An integer programming model is developed for order selection and test bed scheduling but it cannot handle large problems in a reasonable amount of time. Consequently, a hybrid genetic algorithm (GA) is suggested to solve the developed model. Several experiments have been carried out to demonstrate the performance of the proposed hybrid GA in scheduling test beds. The results show that the hybrid GA performs with an outstanding run-time and small errors in comparison with the integer programming model. |
| Databáze: | OpenAIRE |
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