Metaheuristics for the mixed shop scheduling problem

Liu, Shi Qiang & Ong, Hoon Liong (2004) Metaheuristics for the mixed shop scheduling problem. Asia-Pacific Journal of Operational Research, 21(1), pp. 97-115.

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Abstract

In this paper, three metaheuristics are proposed for solving a class of job shop, open shop, and mixed shop scheduling problems. We evaluate the performance of the proposed algorithms by means of a set of Lawrence’s benchmark instances for the job shop problem, a set of randomly generated instances for the open shop problem, and a combined job shop and open shop test data for the mixed shop problem. The computational results show that the proposed algorithms perform extremely well on all these three types of shop scheduling problems. The results also reveal that the mixed shop problem is relatively easier to solve than the job shop problem due to the fact that the scheduling procedure becomes more flexible by the inclusion of more open shop jobs in the mixed shop.

Impact and interest:

12 citations in Scopus
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13 citations in Web of Science®

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ID Code: 48681
Item Type: Journal Article
Refereed: Yes
Keywords: Machine scheduling, open shop, job shop, mixed shop, metaheuristics
DOI: 10.1142/S0217595904000072
ISSN: 0217-5959
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > APPLIED MATHEMATICS (010200) > Operations Research (010206)
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 06 Feb 2014 23:23
Last Modified: 06 Feb 2014 23:23

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