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A genetic algorithm for minimizing energy consumption in warehouses

dc.contributor.buuauthorEne, Seval
dc.contributor.buuauthorKüçükoğlu, İlker
dc.contributor.buuauthorAksoy, Aslı
dc.contributor.buuauthorÖztürk, Nursel
dc.contributor.departmentMühendislik Fakültesi
dc.contributor.departmentEndüstri Mühendisliği Bölümü
dc.contributor.orcid0000-0002-2971-2701
dc.contributor.orcid0000-0002-5075-0876
dc.contributor.researcheridD-8543-2015
dc.contributor.researcheridAAG-9235-2021
dc.contributor.researcheridAAG-8949-2021
dc.contributor.researcheridAAG-9336-2021
dc.contributor.scopusid48461146800
dc.contributor.scopusid55763879600
dc.contributor.scopusid35221094400
dc.contributor.scopusid7005688805
dc.date.accessioned2022-10-18T08:29:03Z
dc.date.available2022-10-18T08:29:03Z
dc.date.issued2016-11-01
dc.description.abstractGreen supply chain Management is generally defined as integration of green thinking and environmental issues into the whole supply chain operations like product design, manufacturing process, warehousing, distribution etc. Within this context green principles should be adopted in warehouse management to minimize negative impact on the environment. In warehouse operations, picking must be analyzed attentively which is widely studied in literature for minimizing service time levels because of its close relation to the higher costs. The efficiency of picking in warehouses mainly depends on storage assignment policy that directly affects picking performance in warehouses. In this paper, picking operation in warehouses is studied to minimize energy consumption with proper storage policy other than service time. Genetic algorithm (GA) is proposed to solve the problem and numerical examples are presented to demonstrate the performance of the GA. Results show that, the GA gives efficient solutions to the problem.
dc.identifier.citationEne, S. vd. (2016). "A genetic algorithm for minimizing energy consumption in warehouses". Energy, 114, 973-980.
dc.identifier.endpage980
dc.identifier.issn0360-5442
dc.identifier.issn1873-6785
dc.identifier.scopus2-s2.0-84984618945
dc.identifier.startpage973
dc.identifier.urihttps://doi.org/10.1016/j.energy.2016.08.045
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0360544216311586
dc.identifier.urihttp://hdl.handle.net/11452/29132
dc.identifier.volume114
dc.identifier.wos000387194800077
dc.indexed.wosSCIE
dc.language.isoen
dc.publisherPergamon-Elsevier Science
dc.relation.bapKUAP(M)-2012/53
dc.relation.journalEnergy
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectThermodynamics
dc.subjectEnergy & fuels
dc.subjectGenetic algorithm
dc.subjectGreen supply chain
dc.subjectMinimization of energy consumption
dc.subjectWarehouse management
dc.subjectOrder-picking
dc.subjectStorage assignment
dc.subjectTravel distance
dc.subjectPolicies
dc.subjectDesign
dc.subjectGreen
dc.subjectAlgorithms
dc.subjectEnergy policy
dc.subjectEnergy utilization
dc.subjectGenetic algorithms
dc.subjectIndustrial management
dc.subjectProduct design
dc.subjectSupply chain management
dc.subjectEnvironmental issues
dc.subjectGreen supply chain
dc.subjectGreen supply chain management
dc.subjectImpact on the environment
dc.subjectManufacturing process
dc.subjectStorage assignment policies
dc.subjectSupply chain operation
dc.subjectWarehouse management
dc.subjectEnergy conservation
dc.subjectEnvironmental issue
dc.subjectGenetic algorithm
dc.subjectManufacturing
dc.subjectSupply chain management
dc.subjectWarehouses
dc.subject.scopusInformation Retrieval; AS/RS; Warehouses
dc.subject.wosThermodynamics
dc.subject.wosEnergy & fuels
dc.titleA genetic algorithm for minimizing energy consumption in warehouses
dc.typeArticle
dc.wos.quartileQ1
dspace.entity.typePublication
local.contributor.departmentMühendislik Fakültesi/Endüstri Mühendisliği Bölümü
local.indexed.atScopus
local.indexed.atWOS

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