Scheduling parallel-batching processing machines problem with learning and deterioration effect in fuzzy environment

In this paper, a problem of scheduling jobs with different sizes and fuzzy processing times (FPT) on non-identical parallel batch machines to minimize makespan is investigated. Moreover, the processing time (PT) of each batch is subject to the location-based learning and total-PT-based deterioration...

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Bibliographic Details
Published inJournal of intelligent & fuzzy systems Vol. 40; no. 6; pp. 12111 - 12124
Main Authors Wang, Rui, Jia, Zhaohong, Li, Kai
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.01.2021
Sage Publications Ltd
Subjects
Algorithms
Combinatorial analysis
Deterioration
Fuzzy logic
Fuzzy sets
Learning
Optimization
Scheduling
scheduling
combinatorial optimization
fuzzy sets
Evolutionary algorithms
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Summary:In this paper, a problem of scheduling jobs with different sizes and fuzzy processing times (FPT) on non-identical parallel batch machines to minimize makespan is investigated. Moreover, the processing time (PT) of each batch is subject to the location-based learning and total-PT-based deterioration effect. Since this is an NP-hard combinatorial optimization problem, an improved intelligent algorithm based on fruit fly optimization algorithm (IFOA) is proposed. To verify the performance of the algorithm, the IFOA is compared with three state-of-the-art algorithms. The comparative results demonstrate that the proposed IFOA outperforms the other compared algorithms.
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ISSN:1064-1246
1875-8967
DOI:10.3233/JIFS-210196