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The Use of Chance Constrained Programming for Disassemble-to-Order Problems with Stochastic Yields

In: Operations Research Proceedings 2006

Author

Listed:
  • Ian M. Langella

    (Otto-von-Guericke University)

  • Rainer Kleber

    (Otto-von-Guericke University)

Abstract

Stochastic yields from disassembly complicate the planning of so-called disassemble to order problems, where a specified amount of components must be harvested from various models of returned products. Chance constraint programming, a branch of stochastic programming, has proven useful in several applications of operations management. This contribution will first formulate a novel chance constrained programming model for the single-period disassemble-to-order problem. We will then illustrate its application using an example, and highlight the tradeoff between service and costs which emerges. We also suggest a variety of extensions to the basic model, many of which will likely prove to be trivial and relevant to industry.

Suggested Citation

  • Ian M. Langella & Rainer Kleber, 2007. "The Use of Chance Constrained Programming for Disassemble-to-Order Problems with Stochastic Yields," Operations Research Proceedings, in: Karl-Heinz Waldmann & Ulrike M. Stocker (ed.), Operations Research Proceedings 2006, pages 473-478, Springer.
    • Handle: RePEc:spr:oprchp:978-3-540-69995-8_75
    DOI: 10.1007/978-3-540-69995-8_75
    as

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