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Implementation of an Ant Colony Optimization technique for job shop scheduling problem
- Issue Date
- Mar-2006
- Publisher
- SAGE Publications
- Keywords
- job shop scheduling problem (JSP); Ant Colony System (ACS); Ant Colony Optimization (ACO); natural computation (NC)
- Citation
- Transactions of the Institute of Measurement and Control, v.28, no.1, pp 93 - 108
- Pages
- 16
- Indexed
- SCIE
SCOPUS
- Journal Title
- Transactions of the Institute of Measurement and Control
- Volume
- 28
- Number
- 1
- Start Page
- 93
- End Page
- 108
- ISSN
- 0142-3312
1477-0369
- Abstract
- Research on optimization of the job shop scheduling problem (JSP) is one of the most significant and promising areas of optimization. Instead of the traditional optimization method, this paper presents an investigation into the use of an Ant Colony System (ACS) to optimize the JSP. The main characteristics of this system are positive feedback, distributed computation, robustness and the use of a constructive greedy heuristic. In this paper, an improvement of the performance of ACS will be discussed. The numerical experiments of ACS were implemented in a small JSP. The optimized results of the ACS are favourably compared with the traditional optimization methods.
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Related Researcher
- ZHANG, Jun
- ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)