• Title/Summary/Keyword: Two-stage stochastic LP

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Analysis on Upper and Lower Bounds of Stochastic LP Problems (확률적 선형계획문제의 상한과 하한한계 분석)

  • 이상진
    • Journal of the Korean Operations Research and Management Science Society
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    • v.27 no.3
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    • pp.145-156
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    • 2002
  • Business managers are often required to use LP problems to deal with uncertainty inherent in decision making due to rapid changes in today's business environments. Uncertain parameters can be easily formulated in the two-stage stochastic LP problems. However, since solution methods are complex and time-consuming, a common approach has been to use modified formulations to provide upper and lower bounds on the two-stage stochastic LP problem. One approach is to use an expected value problem, which provides upper and lower bounds. Another approach is to use “walt-and-see” problem to provide upper and lower bounds. The objective of this paper is to propose a modified approach of “wait-and-see” problem to provide an upper bound and to compare the relative error of optimal value with various upper and lower bounds. A computing experiment is implemented to show the relative error of optimal value with various upper and lower bounds and computing times.

A Study on Solution Methods of Two-stage Stochastic LP Problems

  • Lee, Sang-Jin
    • Journal of the Korean Operations Research and Management Science Society
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    • v.22 no.1
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    • pp.1-24
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    • 1997
  • In this paper, we have proposed new solution methods to solve TSLP (two-stage stochastic linear programming) problems. One solution method is to combine the analytic center concept with Benders' decomposition strategy to solve TSLP problems. Another method is to apply an idea proposed by Geoffrion and Graves to modify the L-shaped algorithm and the analytic center algorithm. We have compared the numerical performance of the proposed algorithms to that of the existing algorithm, the L-shaped algorithm. To effectively compare those algorithms, we have had computational experiments for seven test problems.

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