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Article: Simulation-based optimization for material handling systems in manufacturing and distribution industries

TitleSimulation-based optimization for material handling systems in manufacturing and distribution industries
Authors
KeywordsArtificial immune system
Artificial intelligence
Material handling system
Optimization
Simulation
Issue Date2020
PublisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=1022-0038
Citation
Wireless Networks, 2020, v. 26 n. 7, p. 4839-4860 How to Cite?
AbstractFaced with rising customer expectations, shortening product life cycle and increasing number of competitors, many companies are paying increasing attention to streamline their operations with a view to improving the timeliness in response to changes and demands in their supply chains. Material handling is a vital element of the supply chains, which involves a variety of operations including the movement, storage, protection and control of materials and products throughout the processes of manufacturing and distribution. Having efficient material handling systems is of great importance to these industries for maintaining and facilitating a continuous flow of materials through the workplace and guaranteeing that required materials are available when needed. In this paper, we apply a simulation-based optimization framework for solving several real-life single objective and multi-objective optimization problems. The results reveal that the simulation-based optimization framework could become an effective decision making tool for solving both single and multi-objective optimization problems in manufacturing and distribution industries and help management to find near-optimal system parameters to fulfill important objectives.
Persistent Identifierhttp://hdl.handle.net/10722/272203
ISSN
2021 Impact Factor: 2.701
2020 SCImago Journal Rankings: 0.417
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLeung, CSK-
dc.contributor.authorLau, HYK-
dc.date.accessioned2019-07-20T10:37:41Z-
dc.date.available2019-07-20T10:37:41Z-
dc.date.issued2020-
dc.identifier.citationWireless Networks, 2020, v. 26 n. 7, p. 4839-4860-
dc.identifier.issn1022-0038-
dc.identifier.urihttp://hdl.handle.net/10722/272203-
dc.description.abstractFaced with rising customer expectations, shortening product life cycle and increasing number of competitors, many companies are paying increasing attention to streamline their operations with a view to improving the timeliness in response to changes and demands in their supply chains. Material handling is a vital element of the supply chains, which involves a variety of operations including the movement, storage, protection and control of materials and products throughout the processes of manufacturing and distribution. Having efficient material handling systems is of great importance to these industries for maintaining and facilitating a continuous flow of materials through the workplace and guaranteeing that required materials are available when needed. In this paper, we apply a simulation-based optimization framework for solving several real-life single objective and multi-objective optimization problems. The results reveal that the simulation-based optimization framework could become an effective decision making tool for solving both single and multi-objective optimization problems in manufacturing and distribution industries and help management to find near-optimal system parameters to fulfill important objectives.-
dc.languageeng-
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=1022-0038-
dc.relation.ispartofWireless Networks-
dc.subjectArtificial immune system-
dc.subjectArtificial intelligence-
dc.subjectMaterial handling system-
dc.subjectOptimization-
dc.subjectSimulation-
dc.titleSimulation-based optimization for material handling systems in manufacturing and distribution industries-
dc.typeArticle-
dc.identifier.emailLau, HYK: hyklau@hku.hk-
dc.identifier.authorityLau, HYK=rp00137-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s11276-018-1894-x-
dc.identifier.scopuseid_2-s2.0-85057621146-
dc.identifier.hkuros298268-
dc.identifier.volume26-
dc.identifier.issue7-
dc.identifier.spage4839-
dc.identifier.epage4860-
dc.identifier.isiWOS:000563175500009-
dc.publisher.placeUnited States-
dc.identifier.issnl1022-0038-

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