A discrete artificial bee colony algorithm for the permutation flow shop scheduling problem with total flowtime criterion

dc.contributor.author M. Fatih Tasgetiren
dc.contributor.author Quanke Pan
dc.contributor.author Ponnuthurai Nagaratnam Suganthan
dc.contributor.author Angela Hsiang Ling Chen
dc.date.accessioned 2025-10-06T17:53:09Z
dc.date.issued 2010
dc.description.abstract Very recently Jarboui et al. [1] (Computers & Operations Research 36 (2009) 2638-2646) and Tseng and Lin [2] (European Journal of Operational Research 198 (2009) 84-92) presented a novel estimation distribution algorithm (EDA) and a hybrid genetic local search (hGLS) algorithm for the permutation flowshop scheduling (PFSP) with the total flowtime (TFT) criterion respectively. Both algorithms generated excellent results thus improving all the best known solutions reported in the literature so far. However in this paper we present a discrete artificial bee colony (DABC) algorithm hybridized with an iterated greedy (IG) and iterated local search (ILS) algorithms embedded in a variable neighborhood search (VNS) procedure based on swap and insertion neighborhood structures. We also present a hybrid version of our previous discrete differential evolution (hDDE) algorithm employing the IG and VNS structure too. The performance of the DABC and hDDE is highly competitive to the EDA and hGLS algorithms in terms of both solution quality and CPU times. Ultimately 43 out of 60 best known solutions provided very recently by the EDA and hGLS algorithms are further improved by the DABC and hDDE algorithms with short-term search. © 2010 IEEE. © 2011 Elsevier B.V. All rights reserved.
dc.identifier.doi 10.1109/CEC.2010.5586300
dc.identifier.isbn 9781424469109
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-79959466769&doi=10.1109%2FCEC.2010.5586300&partnerID=40&md5=48b29961554b5650bf32cd8c1b89b939
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/10270
dc.language.iso English
dc.relation.ispartof 2010 6th IEEE World Congress on Computational Intelligence WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation CEC 2010
dc.subject Artificial Bee Colonies, Cpu Time, Differential Evolution, Distribution Algorithms, Hybrid Genetic, Iterated Local Search, Neighborhood Structure, Operational Research, Permutation Flow-shop Scheduling, Solution Quality, Total Flowtime, Variable Neighborhood Search, Artificial Intelligence, Biology, Evolutionary Algorithms
dc.subject Artificial bee colonies, CPU time, Differential Evolution, Distribution algorithms, Hybrid genetic, Iterated local search, Neighborhood structure, Operational research, Permutation flow-shop scheduling, Solution quality, Total flowtime, Variable neighborhood search, Artificial intelligence, Biology, Evolutionary algorithms
dc.title A discrete artificial bee colony algorithm for the permutation flow shop scheduling problem with total flowtime criterion
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person.identifier.scopus-author-id Tasgetiren- M. Fatih (6505799356), Pan- Quanke (15074237600), Suganthan- Ponnuthurai Nagaratnam (7003996538), Chen- Angela Hsiang Ling (55369384200)
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