A fuzzy stochastic multi-objective optimization model to configure a supply chain considering new product development
•Designing a multi objective multi period multi product supply chain model.•Considering the SC configuration and the NPD simultaneously.•Optimum lunching time of new products with fuzzy stochastic model. This study aims to design a multi-echelon, multi-objective supply chain model that incorporates...
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| Veröffentlicht in: | Applied mathematical modelling Jg. 40; H. 17-18; S. 7545 - 7570 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Inc
01.09.2016
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| Schlagworte: | |
| ISSN: | 0307-904X |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | •Designing a multi objective multi period multi product supply chain model.•Considering the SC configuration and the NPD simultaneously.•Optimum lunching time of new products with fuzzy stochastic model.
This study aims to design a multi-echelon, multi-objective supply chain model that incorporates new product development and its effects on supply chain configuration. To survive in a highly competitive industry, strategies to either collaborate or compete with rival firms within a network should be considered in the new product development process, and it is crucial to pay great attention to customers’ needs and interests. Considering the imprecise nature of some critical parameters plays an important role in making suitable strategic decisions. This fact requires considering uncertainties of the environment such as customer demands and supplier capacities. In this study, a supply chain involving multiple suppliers, manufacturers, distributors and customers and addressing a multi-objective, multi-period and multi-product aggregate procurement and production planning problem is considered. The first objective function aims to maximize the profit of the supply chain, including that associated with new product development. The second objective function considers customer satisfaction, and the third one maximizes the production of the developed and new products. To address real-world planning problems involving noisy, incomplete or erroneous data, the supplier capacity parameters of the supply chain and demand fluctuations are subject to uncertainty, which is modeled by fuzzy stochastic programming. Finally, the proposed multi-objective model is solved as a single-objective mixed integer programming model by applying the revised multi-choice goal programming method. In addition, a numerical example is provided to demonstrate the applicability of the proposed model. |
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| ISSN: | 0307-904X |
| DOI: | 10.1016/j.apm.2016.03.015 |