Please use this identifier to cite or link to this item: https://doi.org/10.1142/S0217595904000072
Title: Metaheuristics for the mixed shop scheduling problem
Authors: Liu, S.Q.
Ong, H.L. 
Keywords: Job shop
Machine scheduling
Metaheuristics
Mixed shop
Open shop
Issue Date: Mar-2004
Source: Liu, S.Q., Ong, H.L. (2004-03). Metaheuristics for the mixed shop scheduling problem. Asia-Pacific Journal of Operational Research 21 (1) : 97-115. ScholarBank@NUS Repository. https://doi.org/10.1142/S0217595904000072
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.
Source Title: Asia-Pacific Journal of Operational Research
URI: http://scholarbank.nus.edu.sg/handle/10635/63183
ISSN: 02175959
DOI: 10.1142/S0217595904000072
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