Sustainable stochastic production and procurement problem for resilient supply chain. (January 2020)

• Record Type: Journal Article
• Authors: Kaur, Harpreet; Singh, Surya Prakash; Garza-Reyes, Jose Arturo; Mishra, Nishikant
• Is Part Of: Computers & industrial engineering. Volume 139(2020)
• Publication Date: 2020-01
• Subjects: Resilient procurement model -- Product mix -- Sustainability -- Uncertain demand and capacity -- Bill of materials -- Mixed integer linear program (MILP) -- Mixed Integer Non-Linear Program (MINLP) -- Fuzzy-MCDM; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.12.007
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Paper propose a resilient procurement model. Proposed models are formulated as MILP and MINLP. Paper also propose MCDM-Fuzzy based methodology. Proposed models considers uncertain demand and capacity. Abstract: Traditionally business organizations take production and procurement decisions independently. First, the decision is made on product mix and then procurement plan is developed. However, procurement for all the dependent items is computed using bill of material information of independent items. Any market uncertainty in demand of independent items does not only affects production plan but also the procurement process. Also, sustainability is an essential business aspect and must be considered in production and procurement decisions. Hence, there is a need to develop a resilient integrated production and procurement model capable to capture the fluctuating market demand and also uncertainties in production, supplier & carrier capacities. The paper proposes an independent and integrated production and procurement model considering sustainability and uncertainty for a resilient supply chain. Various possible uncertainties such as market demand, machine capacity, supplier and carrier capacities in the presence of carbon emissions is also considered in the proposed models. The paper also proposed a supplier selection model under uncertainty using Fuzzy-MCDM techniques. The proposed models are MILP & MINLP, and are demonstrated using numerical illustrations solved in LINGO 10. The performance analysis is also conducted and it is found that the integrated model will always provide a more efficient optimal solution while traditional independent production & procurement models may even lead to infeasible solution.