Stochastic Programming in Supply Chain

Stochastic Programming in Supply Chain

Mahdi Hamzeei (University of Wisconsin-Madison, USA) and Narges Kazemzadeh (Iowa State University, USA)
DOI: 10.4018/978-1-61350-504-5.ch014
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Abstract

In today’s global market, Supply Chain Management provides a framework on which decision makers can prepare a production or service network to be more competitive. The huge number of decisions as well as the underlying uncertainty make this system too complex. Stochastic programming as an optimization technique, which incorporates uncertainty in decisions, has been employed in this area. In this chapter, the authors will investigate some applications of stochastic programming in Supply Chain. The authors also explain briefly about stochastic programming.
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2 Two-Stage Stochastic Linear Program

In this section, we will mainly explain methods developed for solving the two-stage stochastic programs. Note that this area of knowledge is too vast to be explained in one chapter. That is, it only suffices for us to have a brief review.

First, we look at the general form of two-stage linear programs. Then, we will explain the three main methods, including L-Shape method, Lagrangian relaxation and Sample Average Approximation, have been proposed for solving the problem.

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