A bi-level decision-making system to optimize a robust-resilient-sustainable aggregate production planning problem
This study introduces a sustainable-robust aggregate production planning (APP) problem taking into account workforce productivity, outsourcing option and supplier resilience. In this regard, a bi-level decision-making system is designed using multi-attribute decision-making (MADM) and multi-objectiv...
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| Vydáno v: | Expert systems with applications Ročník 228; s. 120476 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
15.10.2023
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| ISSN: | 0957-4174, 1873-6793 |
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| Abstract | This study introduces a sustainable-robust aggregate production planning (APP) problem taking into account workforce productivity, outsourcing option and supplier resilience. In this regard, a bi-level decision-making system is designed using multi-attribute decision-making (MADM) and multi-objective decision-making (MODM) models, respectively. In the MADM section, a hybrid method called BWM-WASPAS-Neutrosophic based on best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) under type-2 neutrosophic number (T2NN) is utilized to investigate resilient supplier selection. To design the MODM section, a multi-objective mixed-integer linear programming (MILP) model is suggested which is then treated with the help of weighted goal programming (WGP) method. The multi-objective model honors sustainable development goals as it aims not only to minimize total cost and maximize weighted purchasing from suppliers, but also to minimize negative environmental impacts simultaneously. Robust optimization (RO) technique is then implemented to the MODM model to address the demand uncertainty. In order to validate the suggested methodology, a real case study from the literature is examined. The obtained results reveal the efficiency of our decision-making system in finding the optimal policy in less than 1 s where sensitivity analyses also contribute to practical managerial implications. Finally, it is revealed that the total weighted purchase from suppliers has the highest sensitivity to the conservatism levels, which determine the extent to which our uncertain demand parameter can deviate from its nominal value. |
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| AbstractList | This study introduces a sustainable-robust aggregate production planning (APP) problem taking into account workforce productivity, outsourcing option and supplier resilience. In this regard, a bi-level decision-making system is designed using multi-attribute decision-making (MADM) and multi-objective decision-making (MODM) models, respectively. In the MADM section, a hybrid method called BWM-WASPAS-Neutrosophic based on best-worst method (BWM) and weighted aggregated sum-product assessment (WASPAS) under type-2 neutrosophic number (T2NN) is utilized to investigate resilient supplier selection. To design the MODM section, a multi-objective mixed-integer linear programming (MILP) model is suggested which is then treated with the help of weighted goal programming (WGP) method. The multi-objective model honors sustainable development goals as it aims not only to minimize total cost and maximize weighted purchasing from suppliers, but also to minimize negative environmental impacts simultaneously. Robust optimization (RO) technique is then implemented to the MODM model to address the demand uncertainty. In order to validate the suggested methodology, a real case study from the literature is examined. The obtained results reveal the efficiency of our decision-making system in finding the optimal policy in less than 1 s where sensitivity analyses also contribute to practical managerial implications. Finally, it is revealed that the total weighted purchase from suppliers has the highest sensitivity to the conservatism levels, which determine the extent to which our uncertain demand parameter can deviate from its nominal value. |
| ArticleNumber | 120476 |
| Author | Mahdavi, Iraj Tirkolaee, Erfan Babaee Aydin, Nadi Serhan |
| Author_xml | – sequence: 1 givenname: Erfan Babaee orcidid: 0000-0003-1664-9210 surname: Tirkolaee fullname: Tirkolaee, Erfan Babaee email: erfan.babaee@istinye.edu.tr organization: Department of Industrial Engineering, Istinye University, 34396 Istanbul, Turkey – sequence: 2 givenname: Nadi Serhan orcidid: 0000-0002-1453-0016 surname: Aydin fullname: Aydin, Nadi Serhan email: serhan.aydin@istinye.edu.tr organization: Department of Industrial Engineering, Istinye University, 34396 Istanbul, Turkey – sequence: 3 givenname: Iraj orcidid: 0000-0001-5123-6169 surname: Mahdavi fullname: Mahdavi, Iraj organization: Department of Industrial Engineering, Mazandaran University of Science & Technology, Babol, Iran |
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| Keywords | Resilient supplier selection Sustainable aggregate production planning Workforce productivity Robust optimization BWM-WASPAS-Neutrosophic Bi-level decision-making system |
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| SubjectTerms | Bi-level decision-making system BWM-WASPAS-Neutrosophic Resilient supplier selection Robust optimization Sustainable aggregate production planning Workforce productivity |
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