A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSO
Nowadays, rapid changes in customers' demands have redoubled the importance of new concepts such as supply chain flexibility and its application. The extent to which flexibility should be built into supply chains requires full consideration. Flexibility is defined as firms' quick and effic...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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University of Novi Sad, Faculty of Technical Sciences
2022-03-01
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| Series: | International Journal of Industrial Engineering and Management |
| Subjects: | |
| Online Access: | http://www.ijiemjournal.uns.ac.rs/images/journal/volume13/IJIEM_298.pdf |
| _version_ | 1819280818528321536 |
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| author | Sara Khorsandi Karimi Seyed Jafar Sadjadi Seyed Gholamreza Jalali Naini |
| author_facet | Sara Khorsandi Karimi Seyed Jafar Sadjadi Seyed Gholamreza Jalali Naini |
| author_sort | Sara Khorsandi Karimi |
| collection | DOAJ |
| description | Nowadays, rapid changes in customers' demands have redoubled the importance of new concepts such as supply chain flexibility and its application. The extent to which flexibility should be built into supply chains requires full consideration. Flexibility is defined as firms' quick and efficient response to changes. This paper quantifies the positive effects of adding different flexibility dimensions to a production planning bi-objective mathematical model. Four flexibility dimensions are proposed according to the needs of a production plant chosen as the case study. The objective functions are to minimize total costs along with the delivery time of the product, respectively. We also employ two metaheuristic algorithms, NSGA-Ⅱ and MOPSO, to solve our proposed NP-hard model. Afterwards, we compare both solution strategies based on five criteria to achieve optimal results. Moreover, we compare the performance of both flexible and inflexible models in terms of costs. The results show that applying the flexible model causes a reduction of %22 in costs. |
| first_indexed | 2024-12-24T00:49:50Z |
| format | Article |
| id | doaj.art-287a09a9341c40b9b3c4de4d909fd44e |
| institution | Directory Open Access Journal |
| issn | 2217-2661 2683-345X |
| language | English |
| last_indexed | 2024-12-24T00:49:50Z |
| publishDate | 2022-03-01 |
| publisher | University of Novi Sad, Faculty of Technical Sciences |
| record_format | Article |
| series | International Journal of Industrial Engineering and Management |
| spelling | doaj.art-287a09a9341c40b9b3c4de4d909fd44e2022-12-21T17:23:36ZengUniversity of Novi Sad, Faculty of Technical SciencesInternational Journal of Industrial Engineering and Management2217-26612683-345X2022-03-011311837http://doi.org/10.24867/IJIEM-2022-1-298298A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSOSara Khorsandi Karimi0Seyed Jafar Sadjadi1Seyed Gholamreza Jalali Naini2Department of Industrial Engineering, Iran University of Science and Technology, Tehran, IranDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, IranDepartment of Industrial Engineering, Iran University of Science and Technology, Tehran, IranNowadays, rapid changes in customers' demands have redoubled the importance of new concepts such as supply chain flexibility and its application. The extent to which flexibility should be built into supply chains requires full consideration. Flexibility is defined as firms' quick and efficient response to changes. This paper quantifies the positive effects of adding different flexibility dimensions to a production planning bi-objective mathematical model. Four flexibility dimensions are proposed according to the needs of a production plant chosen as the case study. The objective functions are to minimize total costs along with the delivery time of the product, respectively. We also employ two metaheuristic algorithms, NSGA-Ⅱ and MOPSO, to solve our proposed NP-hard model. Afterwards, we compare both solution strategies based on five criteria to achieve optimal results. Moreover, we compare the performance of both flexible and inflexible models in terms of costs. The results show that applying the flexible model causes a reduction of %22 in costs.http://www.ijiemjournal.uns.ac.rs/images/journal/volume13/IJIEM_298.pdfflexibilitysupply chainoptimizationnsga-ⅱmopsometaheuristic methods |
| spellingShingle | Sara Khorsandi Karimi Seyed Jafar Sadjadi Seyed Gholamreza Jalali Naini A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSO International Journal of Industrial Engineering and Management flexibility supply chain optimization nsga-ⅱ mopso metaheuristic methods |
| title | A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSO |
| title_full | A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSO |
| title_fullStr | A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSO |
| title_full_unstemmed | A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSO |
| title_short | A bi-objective production planning for a flexible supply chain solved using NSGA-II and MOPSO |
| title_sort | bi objective production planning for a flexible supply chain solved using nsga ii and mopso |
| topic | flexibility supply chain optimization nsga-ⅱ mopso metaheuristic methods |
| url | http://www.ijiemjournal.uns.ac.rs/images/journal/volume13/IJIEM_298.pdf |
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