An analogue genetic algorithm for solving job shop scheduling problems
Article
Article Title | An analogue genetic algorithm for solving job shop scheduling problems |
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ERA Journal ID | 3609 |
Article Category | Article |
Authors | |
Author | Al-Hakim, Latif |
Journal Title | International Journal of Production Research |
Journal Citation | 39 (7), pp. 1537-1548 |
Number of Pages | 12 |
Year | 2001 |
Place of Publication | United Kingdom |
ISSN | 0020-7543 |
1366-588X | |
Digital Object Identifier (DOI) | https://doi.org/10.1080/00207540010023538 |
Web Address (URL) | http://www.informaworld.com/smpp/ftinterface~content=a713846023~fulltext=713240930 |
Abstract | This paper develops a genetic algorithm for solving job shop scheduling problems. It discusses the difficulties arising from the traditional encoding of the problem and suggests a new encoding scheme. The paper also develops an analogue electrical system to represent the problem and uses the measure of that system to develop a new measure for the fitness function of the genetic algorithm. The algorithm considers the conventional genetic operations but with some modification. The computational results, developed for the makespan criterion, show that, for this criterion, the algorithm is reliable and performs relatively well. |
Keywords | job shops, shop scheduling, analogue algorithms |
ANZSRC Field of Research 2020 | 401499. Manufacturing engineering not elsewhere classified |
359999. Other commerce, management, tourism and services not elsewhere classified | |
Byline Affiliations | Department of Management and Organisational Behaviour |
https://research.usq.edu.au/item/9y4q6/an-analogue-genetic-algorithm-for-solving-job-shop-scheduling-problems
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