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Interactive Multi-Objective Stochastic Programming Approaches for Designing Robust Supply Chain Networks

In: Operations Research Proceedings 2008

Author

Listed:
  • Amir Azaron

    (University of Karlsruhe (TH))

  • Kai Furmans

    (University of Karlsruhe (TH))

  • Mohammad Modarres

    (Sharif University of Technology)

Abstract

Summary Many attempts have been made to model and optimize supply chain design, most of which are based on deterministic approaches, see for example [3], [8], [4] and many others. In order to take into account the effects of the uncertainty in the production scenario, a two-stage stochastic model is proposed in this paper. There are a few research works addressing comprehensive (strategic and tactical issues simultaneously) design of supply chain networks using two-stage stochastic models including [6], [9], [1] and [7]. [2] developed a multi-objective stochastic programming approach for designing robust supply chains. Then, they used goal attainment technique, see [5] for details, to solve the resulting multi-objective problem. This method has the same disadvantages as those of goal programming; namely, the preferred solution is sensitive to the goal vector and the weighting vector given by the decision maker, and it is very hard in practice to get the proper goals and weights. To overcome this drawback, we use STEM method in this paper to solve this multi-objective model.

Suggested Citation

  • Amir Azaron & Kai Furmans & Mohammad Modarres, 2009. "Interactive Multi-Objective Stochastic Programming Approaches for Designing Robust Supply Chain Networks," Springer Books, in: Bernhard Fleischmann & Karl-Heinz Borgwardt & Robert Klein & Axel Tuma (ed.), Operations Research Proceedings 2008, chapter 28, pages 173-178, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-00142-0_28
    DOI: 10.1007/978-3-642-00142-0_28
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