A method for a robust optimization of joint product and supply chain design

Bertrand Baud-Lavigne (), Samuel Bassetto () and Bruno Agard ()
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Bertrand Baud-Lavigne: École Polytechnique de Montréal
Samuel Bassetto: École Polytechnique de Montréal
Bruno Agard: École Polytechnique de Montréal

Journal of Intelligent Manufacturing, 2016, vol. 27, issue 4, No 3, 749 pages

Abstract: Abstract This paper proposes a method for finding a robust solution to the problem of joint product family and supply chain design. Optimizing product design and the supply chain network at the same time brings substantial benefits. However, this approach involves decisions that can generate uncertainties in the long term. The challenge is to come up with a method that can adapt to most possible environments without straying too far from the optimal solution. Our approach is based on the generation of scenarios that correspond to combinations of uncertain parameters within the model. The performance of designs resulting from these scenario optimizations are compared to the performance of each of the other design scenarios, based on their probability of occurrence. The proposed methodology will allow practitioners to choose a suitable design, from the most profitable to the most reliable.

Keywords: Robust design; Supply chain; Product family; Mixed linear programming (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10845-014-0908-5

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