Multi-objective optimisation in inventory planning with supplier selection
Supplier selection and inventory planning are critical and challenging tasks in Supply Chain Management. There are many studies on both topics and many solution techniques have been proposed dealing with each problem separately. In this study, we present a two-stage integrated approach to the suppli...
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| Format: | Article |
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Elsevier
2017
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| Online Access: | https://eprints.nottingham.ac.uk/40426/ |
| _version_ | 1848796053668626432 |
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| author | Turk, Seda Özcan, Ender John, Robert |
| author_facet | Turk, Seda Özcan, Ender John, Robert |
| author_sort | Turk, Seda |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Supplier selection and inventory planning are critical and challenging tasks in Supply Chain Management. There are many studies on both topics and many solution techniques have been proposed dealing with each problem separately. In this study, we present a two-stage integrated approach to the supplier selection and inventory planning. In the first stage, suppliers are ranked based on various criteria, including cost, delivery, service and product quality using Interval Type-2 Fuzzy Sets (IT2FS)s. In the following stage, an inventory model is created. Then, an Multi-objective Evolutionary Algorithm (MOEA) is utilised simultaneously minimising the conflicting objectives of supply chain operation cost and supplier risk. We evaluated the performance of three MOEAs with tuned parameter settings, namely NSGA-II, SPEA2 and IBEA on a total of twenty four synthetic and real world problem instances. The empirical results show that in the overall, NSGA-II is the best performing MOEA producing high quality trade-off solutions to the integrated problem of supplier selection and inventory planning. |
| first_indexed | 2025-11-14T19:41:52Z |
| format | Article |
| id | nottingham-40426 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:41:52Z |
| publishDate | 2017 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-404262020-05-04T18:55:25Z https://eprints.nottingham.ac.uk/40426/ Multi-objective optimisation in inventory planning with supplier selection Turk, Seda Özcan, Ender John, Robert Supplier selection and inventory planning are critical and challenging tasks in Supply Chain Management. There are many studies on both topics and many solution techniques have been proposed dealing with each problem separately. In this study, we present a two-stage integrated approach to the supplier selection and inventory planning. In the first stage, suppliers are ranked based on various criteria, including cost, delivery, service and product quality using Interval Type-2 Fuzzy Sets (IT2FS)s. In the following stage, an inventory model is created. Then, an Multi-objective Evolutionary Algorithm (MOEA) is utilised simultaneously minimising the conflicting objectives of supply chain operation cost and supplier risk. We evaluated the performance of three MOEAs with tuned parameter settings, namely NSGA-II, SPEA2 and IBEA on a total of twenty four synthetic and real world problem instances. The empirical results show that in the overall, NSGA-II is the best performing MOEA producing high quality trade-off solutions to the integrated problem of supplier selection and inventory planning. Elsevier 2017-07-15 Article PeerReviewed Turk, Seda, Özcan, Ender and John, Robert (2017) Multi-objective optimisation in inventory planning with supplier selection. Expert Systems with Applications, 78 . pp. 51-63. ISSN 0957-4174 Interval type-2 fuzzy; Evolutionary computation; Metaheuristic; Optimisation http://www.sciencedirect.com/science/article/pii/S0957417417300969 doi:10.1016/j.eswa.2017.02.014 doi:10.1016/j.eswa.2017.02.014 |
| spellingShingle | Interval type-2 fuzzy; Evolutionary computation; Metaheuristic; Optimisation Turk, Seda Özcan, Ender John, Robert Multi-objective optimisation in inventory planning with supplier selection |
| title | Multi-objective optimisation in inventory planning with supplier selection |
| title_full | Multi-objective optimisation in inventory planning with supplier selection |
| title_fullStr | Multi-objective optimisation in inventory planning with supplier selection |
| title_full_unstemmed | Multi-objective optimisation in inventory planning with supplier selection |
| title_short | Multi-objective optimisation in inventory planning with supplier selection |
| title_sort | multi-objective optimisation in inventory planning with supplier selection |
| topic | Interval type-2 fuzzy; Evolutionary computation; Metaheuristic; Optimisation |
| url | https://eprints.nottingham.ac.uk/40426/ https://eprints.nottingham.ac.uk/40426/ https://eprints.nottingham.ac.uk/40426/ |