Towards Supply Chain Planning Integration: Uncertainty Analysis Using Fuzzy Mathematical Programming Approach in a Plastic Forming Company

Authors

  • Abdolhamid Safaei Ghadikolaei Department of Industrial Management, Faculty of Economics and Administrative Science, University of Mazandaran, Babolsar, Iran
  • Mehrdad Madhoushi Department of Industrial Management, Faculty of Economics and Administrative Science, University of Mazandaran, Babolsar, Iran
  • Yaser Nemati Department of Industrial Management, Faculty of Economics and Administrative Science, University of Mazandaran, Babolsar, Iran
Abstract:

Affected by globalization and increased complexity, supply chain managers have learned about the importance of Sales and Operations Planning (S&OP). However, in large scale supply chains, S&OP has received little attention, by both academics and practitioners. The purpose of this manuscript is to investigate the advantages of S&OP process using a mathematical modeling approach in a large scale plastic forming company. Three Fuzzy Mixed Integer Linear Programming (f-MILP) models were developed in this article for this reason: A Fully Integrated S&OP (FI-S&OP) model, a Partially Integrated S&OP (PI-S&OP) model, and a decoupled planning (DP) model. Also, Triangular Fuzzy Numbers (TFNs) are utilized to represent uncertainty and vagueness associated with real world operations. All the models are developed for a multi-site manufacturing company, which is coping with different raw material suppliers and Third Party Logistics (3PLs), Distribution Centers (DCs), and customers with a wide range of product families. Finally, all the models are applied in a real case in a plastic manufacturing company in Iran. The results demonstrate the superiority of FI-S&OP over other models.

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Journal title

volume 10  issue 2

pages  335- 364

publication date 2017-04-01

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