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https://hdl.handle.net/11499/10460
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Köse, S.Y. | - |
dc.contributor.author | Demir, Leyla | - |
dc.contributor.author | Tunal, S. | - |
dc.contributor.author | Eliiyi, D.T. | - |
dc.date.accessioned | 2019-08-16T13:18:51Z | |
dc.date.available | 2019-08-16T13:18:51Z | |
dc.date.issued | 2015 | - |
dc.identifier.issn | 0305-215X | - |
dc.identifier.uri | https://hdl.handle.net/11499/10460 | - |
dc.identifier.uri | https://doi.org/10.1080/0305215X.2013.875166 | - |
dc.description.abstract | In manufacturing systems, optimal buffer allocation has a considerable impact on capacity improvement. This study presents a simulation optimization procedure to solve the buffer allocation problem in a heat exchanger production plant so as to improve the capacity of the system. For optimization, three metaheuristic-based search algorithms, i.e. a binary-genetic algorithm (B-GA), a binary-simulated annealing algorithm (B-SA) and a binary-tabu search algorithm (B-TS), are proposed. These algorithms are integrated with the simulation model of the production line. The simulation model, which captures the stochastic and dynamic nature of the production line, is used as an evaluation function for the proposed metaheuristics. The experimental study with benchmark problem instances from the literature and the real-life problem show that the proposed B-TS algorithm outperforms B-GA and B-SA in terms of solution quality. © 2014 Taylor and Francis. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Taylor and Francis Ltd. | en_US |
dc.relation.ispartof | Engineering Optimization | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | buffer allocation problem | en_US |
dc.subject | genetic algorithms | en_US |
dc.subject | simulated annealing | en_US |
dc.subject | simulation optimization | en_US |
dc.subject | tabu search | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Benchmarking | en_US |
dc.subject | Learning algorithms | en_US |
dc.subject | Manufacture | en_US |
dc.subject | Optimization | en_US |
dc.subject | Simulated annealing | en_US |
dc.subject | Stochastic models | en_US |
dc.subject | Stochastic systems | en_US |
dc.subject | Tabu search | en_US |
dc.subject | Benchmark-problem instances | en_US |
dc.subject | Binary genetic algorithm | en_US |
dc.subject | Buffer allocation | en_US |
dc.subject | Capacity improvement | en_US |
dc.subject | Optimal buffer allocations | en_US |
dc.subject | Simulated annealing algorithms | en_US |
dc.subject | Simulation optimization | en_US |
dc.subject | Tabu search algorithms | en_US |
dc.subject | Genetic algorithms | en_US |
dc.title | Capacity improvement using simulation optimization approaches: A case study in the thermotechnology industry | en_US |
dc.type | Article | en_US |
dc.identifier.volume | 47 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.startpage | 149 | |
dc.identifier.startpage | 149 | en_US |
dc.identifier.endpage | 164 | en_US |
dc.identifier.doi | 10.1080/0305215X.2013.875166 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopus | 2-s2.0-84924272297 | en_US |
dc.identifier.wos | WOS:000346295300001 | en_US |
dc.identifier.scopusquality | Q1 | - |
dc.owner | Pamukkale University | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.cerifentitytype | Publications | - |
item.openairetype | Article | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.languageiso639-1 | en | - |
crisitem.author.dept | 10.09. Industrial Engineering | - |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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