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Energy-Aware Production Lot-Sizing and Parallel Machine Scheduling With the Product-Specific Machining Tools and Power Requirements

dc.authorid Gurkan, M. Edib/0000-0003-1961-0215
dc.authorscopusid 36988885500
dc.authorscopusid 59223316300
dc.authorscopusid 52263627900
dc.authorwosid Sel, Cagri/B-8597-2016
dc.authorwosid Hamzadayi, Alper/G-3218-2019
dc.authorwosid Gurkan, M. Edib/Hgd-5950-2022
dc.contributor.author Sel, Cagri
dc.contributor.author Gurkan, M. Edib
dc.contributor.author Hamzadayi, Alper
dc.date.accessioned 2025-05-10T17:25:20Z
dc.date.available 2025-05-10T17:25:20Z
dc.date.issued 2024
dc.department T.C. Van Yüzüncü Yıl Üniversitesi en_US
dc.department-temp [Sel, Cagri] Karabuk Univ, Dept Ind Engn, Karabuk, Turkiye; [Gurkan, M. Edib] Karabuk Univ, Dept Management Informat Syst, Karabuk, Turkiye; [Hamzadayi, Alper] Van Yuzuncu Yil Univ, Dept Ind Engn, TR-65080 Van, Turkiye en_US
dc.description Gurkan, M. Edib/0000-0003-1961-0215 en_US
dc.description.abstract This study addresses a multi-product lot-sizing and scheduling problem with sequence-dependent setup times, considering that the machining operations cause energy consumption. The production facility comprises identical parallel machines under which the production of each product requires a certain set of tools. The energy requirement of production depends on the product-specific machining tools. The problem deals with determining the minimum cost lot-sizing and scheduling plan considering the energy capacity of the production facility. We formulate the problem as a mixed integer linear programming model by introducing energy consumption-related costs and constraints. We perform a case study on CNC milling and turning workshops. Further, we propose an heuristic approach combining a decomposition-based Simulated Annealing heuristic and Fix&Optimise algorithms to handle larger-sized problem instances. The computational performance of the proposed heuristic approach is evaluated against the proposed mixed integer linear programming model on a numerical study. Our numerical experiments reveal that the proposed heuristic approach is capable of providing cost-efficient solutions without compromising time efficiency. en_US
dc.description.woscitationindex Science Citation Index Expanded
dc.identifier.doi 10.1016/j.cie.2024.110503
dc.identifier.issn 0360-8352
dc.identifier.issn 1879-0550
dc.identifier.scopus 2-s2.0-85202037100
dc.identifier.scopusquality Q1
dc.identifier.uri https://doi.org/10.1016/j.cie.2024.110503
dc.identifier.uri https://hdl.handle.net/20.500.14720/11326
dc.identifier.volume 196 en_US
dc.identifier.wos WOS:001302838700001
dc.identifier.wosquality Q1
dc.language.iso en en_US
dc.publisher Pergamon-elsevier Science Ltd en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Energy-Aware Planning en_US
dc.subject Lot-Sizing en_US
dc.subject Scheduling en_US
dc.subject Decomposition en_US
dc.subject Simulated Annealing en_US
dc.subject Mip-Based Heuristic en_US
dc.title Energy-Aware Production Lot-Sizing and Parallel Machine Scheduling With the Product-Specific Machining Tools and Power Requirements en_US
dc.type Article en_US

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