Multiobjective Stochastic Linear Programming: An Overview ()

A. Segun Adeyefa, Monga K. Luhandjula

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**DOI: **10.4236/ajor.2011.14023
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Many Optimization problems in engineering and economic involve the challenging task of pondering both conflicting goals and random data. In this paper, we give an up-to-date overview of how important ideas from optimization, probability theory and multicriteria decision analysis are interwoven to address situations where the presence of several objective functions and the stochastic nature of data are under one roof in a linear optimization context. In this way users of these models are not bound to caricature their problems by arbitrarily squeezing different objective functions into one and by blindly accepting fixed values in lieu of imprecise ones.

Keywords

Linear Programming, Multiobjective Programming, Stochastic Programming, Expected Value Optimality/Efficiency, Minimum Risk Solution/Efficiency, Variance Optimality/Efficiency, Optimality/Efficiency with Given Probabilities.

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A. Adeyefa and M. Luhandjula, "Multiobjective Stochastic Linear Programming: An Overview," *American Journal of Operations Research*, Vol. 1 No. 4, 2011, pp. 203-213. doi: 10.4236/ajor.2011.14023.

Conflicts of Interest

The authors declare no conflicts of interest.

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