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

Ian M. Langella () and Rainer Kleber ()
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Ian M. Langella: Otto-von-Guericke University
Rainer Kleber: Otto-von-Guericke University

A chapter in Operations Research Proceedings 2006, 2007, pp 473-478 from Springer

Abstract: 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.

Keywords: Stochastic Programming; Chance Constraint; Chance Constrain Program; Closed Loop Supply Chain; Closed Loop Supply (search for similar items in EconPapers)
Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-540-69995-8_75

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DOI: 10.1007/978-3-540-69995-8_75

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