A hybrid biobjective markov chain based optimization model for sustainable aggregate production planning

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dc.authoridErfan Babaee Tirkolaee / 0000-0003-1664-9210en_US
dc.authoridNadi Serhan Aydın / 0000-0002-1453-0016en_US
dc.authorscopusidErfan Babaee Tirkolaee / 57196032874
dc.authorscopusidNadi Serhan Aydın / 55904216900
dc.authorwosidErfan Babaee Tirkolaee / U-3676-2017en_US
dc.authorwosidNadi Serhan Aydın / X-8938-2018en_US
dc.contributor.authorTirkolaee, Erfan Babaee
dc.contributor.authorAydın, Nadi Serhan
dc.contributor.authorMahdavi, Iraj
dc.date.accessioned2022-11-11T07:52:11Z
dc.date.available2022-11-11T07:52:11Z
dc.date.issued2022en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümüen_US
dc.description.abstractThis research addresses the sustainable aggregate production planning problem by considering the outsourcing option and workforce skill levels as well as taking a Markov process approach for the inventory level. For this purpose, a hybrid biobjective mixed-integer nonlinear programming model featuring a continuous-time Markov chain to accommodate the inventory decision process is developed. The proposed Markov chain approach efficiently describes system dynamics modeling of the production system through a stochastic process. The objective functions are to minimize total cost and total environmental pollution at the same time. To validate the applicability of the methodology and to evaluate the model complexity, three numerical examples are generated based on one of the previous studies in the literature. It is demonstrated that the suggested methodology is able to come up with the final feasible solution based on optimal inventory decisions in less than 65 s. Finally, a number of sensitivity analyses are presented to study the behavior of the objectives under real-world instability and discuss the practical implications and managerial insights. As one of the main findings, it is revealed that the objective functions have no sensitivity to some change intervals of the parameters, which can be analyzed more earnestly by the management in case of the resource allocation process.en_US
dc.identifier.citationTirkolaee, E. B., Aydin, N. S., & Mahdavi, I. (2022). A Hybrid Biobjective Markov Chain Based Optimization Model for Sustainable Aggregate Production Planning. IEEE Transactions on Engineering Management.en_US
dc.identifier.doi10.1109/TEM.2022.3210879en_US
dc.identifier.issn0018-9391en_US
dc.identifier.scopus2-s2.0-85140789048en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TEM.2022.3210879
dc.identifier.uri1558-0040
dc.identifier.urihttps://hdl.handle.net/20.500.12713/3317
dc.identifier.wosWOS:000869383300001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorTirkolaee, Erfan Babaee
dc.institutionauthorAydın, Nadi Serhan
dc.language.isoenen_US
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_US
dc.relation.ispartofIEEE TRANSACTIONS ON ENGINEERING MANAGEMENTen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectProductionen_US
dc.subjectMathematical Modelsen_US
dc.subjectMarkov Processesen_US
dc.subjectCostsen_US
dc.subjectNumerical Modelsen_US
dc.subjectUncertaintyen_US
dc.subjectPlanningen_US
dc.subjectBiobjective Mixed-İnteger Nonlinear Programming (BOMINLP)en_US
dc.subjectMarkov Chainen_US
dc.subjectOutsourcingen_US
dc.subjectStochastic Processen_US
dc.subjectSustainable Aggregate Production Planning (APP)en_US
dc.titleA hybrid biobjective markov chain based optimization model for sustainable aggregate production planningen_US
dc.typeArticleen_US

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