Azizi, N. and Zolfaghari, S. and Liang, M. (2009) Hybrid Simulated Annealing in Flow-shop Scheduling: A Diversification and Intensification Approach. International Journal of Industrial and Systems Engineering, 4 (3). pp. 326-348. ISSN 1748-5037.
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In the last few decades, several effective algorithms to solve combinatorial problems have been proposed. However, the challenging nature of these problems restricts the effectiveness of the conventional techniques. This paper presents a generic framework, SAMED, to tackle combinatorial optimisation problems. Based on this framework, a new algorithm tailored for Flow Shop Scheduling, SAMED-FSS, has been developed. The performance of the proposed method has been compared with other techniques including a conventional simulated annealing, a standard genetic algorithm, and a hybrid genetic algorithm. The computational results clearly indicate that the proposed algorithm is much more efficient than the conventional heuristics. is only available to individual subscribers or to users at subscribing institutions.
|Subjects:||H Social Sciences
H Social Sciences > H Social Sciences (General)
|Divisions:||Faculties > Social Sciences > Kent Business School > Management Science|
|Depositing User:||Cathy Norman|
|Date Deposited:||27 Jul 2012 10:28|
|Last Modified:||27 Jul 2012 13:54|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/29949 (The current URI for this page, for reference purposes)|
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