A robust optimization model for agile and build-to-order supply chain planning under uncertainties

Morteza Lalmazloumian, Kuan Yew Wong, Kannan Govindan () and Devika Kannan
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Morteza Lalmazloumian: Universiti Teknologi Malaysia
Kuan Yew Wong: Universiti Teknologi Malaysia
Kannan Govindan: University of Southern Denmark
Devika Kannan: Aalborg University

Annals of Operations Research, 2016, vol. 240, issue 2, No 4, 435-470

Abstract: Abstract Supply chain planning as one of the most important processes within the supply chain management concept, has a great impact on firms’ success or failure. This paper considers a supply chain planning problem of an agile manufacturing company operating in a build-to-order environment under various kinds of uncertainty. An integrated optimization approach of procurement, production and distribution costs associated with the supply chain members has been taken into account. A robust optimization scenario-based approach is used to absorb the influence of uncertain parameters and variables. The formulation is a robust optimization model with the objective of minimizing the expected total supply chain cost while maintaining customer service level. The developed multi-product, multi-period, multi-echelon robust mixed-integer linear programming model is then solved using the CPLEX optimization studio and guidance related to future areas of research is given.

Keywords: Agile manufacturing; Build-to-order; Supply chain planning; Robust optimization; Mixed-integer linear programming (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (18)

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DOI: 10.1007/s10479-013-1421-5

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