Carbon footprint based multi-objective supplier selection problem with uncertain parameters and fuzzy linguistic preferences
In this paper, we have studied supplier selection Problem (SSP) with reference to carbon footprint associated with the activities of each supplier. Carbon footprint in the proposed model is considered as one of the crucial dimension for the evaluation and selection of the suppliers.. In the problem,...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co. Ltd.
2021-01-01
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| Series: | Sustainable Operations and Computers |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666412721000106 |
| _version_ | 1797976485702664192 |
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| author | Nausheen Hashmi Syed Aqib Jalil Shakeel Javaid |
| author_facet | Nausheen Hashmi Syed Aqib Jalil Shakeel Javaid |
| author_sort | Nausheen Hashmi |
| collection | DOAJ |
| description | In this paper, we have studied supplier selection Problem (SSP) with reference to carbon footprint associated with the activities of each supplier. Carbon footprint in the proposed model is considered as one of the crucial dimension for the evaluation and selection of the suppliers.. In the problem, primary objectives are minimization of the total cost, minimization of rejection, minimization of the late deliveries along with minimization of carbon footprint. These objectives are subjected to some realistic constraints concerning customers’ demand, supplier's capacity, flexibility, allocated budget and accepted amount of carbon footprint. Some parameters in the proposed model are considered to be uncertain values. The proposed multi-objective supplier selection problem with uncertain parameter is solved using fuzzy concept based goal programming approach. The main focus of the proposed model is to deal with human subjectivity by applying the linguistic preference-based method and analyzed the operational effects of supplier selection in terms of environmental efficiency. We have adopted the Expected Constraint programming technique given by Liu (2007) to convert the uncertain parameters into a deterministic one. For the applicability and effectiveness of the model, an illustration has been given in the end. |
| first_indexed | 2024-04-11T04:51:39Z |
| format | Article |
| id | doaj.art-f4d75f850fec47e5aafd6c21ffa65276 |
| institution | Directory Open Access Journal |
| issn | 2666-4127 |
| language | English |
| last_indexed | 2024-04-11T04:51:39Z |
| publishDate | 2021-01-01 |
| publisher | KeAi Communications Co. Ltd. |
| record_format | Article |
| series | Sustainable Operations and Computers |
| spelling | doaj.art-f4d75f850fec47e5aafd6c21ffa652762022-12-27T04:37:26ZengKeAi Communications Co. Ltd.Sustainable Operations and Computers2666-41272021-01-0122029Carbon footprint based multi-objective supplier selection problem with uncertain parameters and fuzzy linguistic preferencesNausheen Hashmi0Syed Aqib Jalil1Shakeel Javaid2Department of Statistics and Operations Research, Aligarh Muslim University, Aligarh 202002, IndiaDepartment of Transportation Management, School of Business, University of Petroleum and Energy Studies (UPES), Dehradun 248007, India; Corresponding author.Department of Statistics and Operations Research, Aligarh Muslim University, Aligarh 202002, IndiaIn this paper, we have studied supplier selection Problem (SSP) with reference to carbon footprint associated with the activities of each supplier. Carbon footprint in the proposed model is considered as one of the crucial dimension for the evaluation and selection of the suppliers.. In the problem, primary objectives are minimization of the total cost, minimization of rejection, minimization of the late deliveries along with minimization of carbon footprint. These objectives are subjected to some realistic constraints concerning customers’ demand, supplier's capacity, flexibility, allocated budget and accepted amount of carbon footprint. Some parameters in the proposed model are considered to be uncertain values. The proposed multi-objective supplier selection problem with uncertain parameter is solved using fuzzy concept based goal programming approach. The main focus of the proposed model is to deal with human subjectivity by applying the linguistic preference-based method and analyzed the operational effects of supplier selection in terms of environmental efficiency. We have adopted the Expected Constraint programming technique given by Liu (2007) to convert the uncertain parameters into a deterministic one. For the applicability and effectiveness of the model, an illustration has been given in the end.http://www.sciencedirect.com/science/article/pii/S2666412721000106Supplier selectionUncertain theoryUncertain variablesCarbon footprintLinguistic preference's |
| spellingShingle | Nausheen Hashmi Syed Aqib Jalil Shakeel Javaid Carbon footprint based multi-objective supplier selection problem with uncertain parameters and fuzzy linguistic preferences Sustainable Operations and Computers Supplier selection Uncertain theory Uncertain variables Carbon footprint Linguistic preference's |
| title | Carbon footprint based multi-objective supplier selection problem with uncertain parameters and fuzzy linguistic preferences |
| title_full | Carbon footprint based multi-objective supplier selection problem with uncertain parameters and fuzzy linguistic preferences |
| title_fullStr | Carbon footprint based multi-objective supplier selection problem with uncertain parameters and fuzzy linguistic preferences |
| title_full_unstemmed | Carbon footprint based multi-objective supplier selection problem with uncertain parameters and fuzzy linguistic preferences |
| title_short | Carbon footprint based multi-objective supplier selection problem with uncertain parameters and fuzzy linguistic preferences |
| title_sort | carbon footprint based multi objective supplier selection problem with uncertain parameters and fuzzy linguistic preferences |
| topic | Supplier selection Uncertain theory Uncertain variables Carbon footprint Linguistic preference's |
| url | http://www.sciencedirect.com/science/article/pii/S2666412721000106 |
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