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A compromise solution for the multiobjective stochastic linear programming under partial uncertainty
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DOI：10.1016/j.ejor.2009.05.019.png)
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Abstract
En 中文
This paper solves the multiobjective stochastic linear program with partially known probability. We address the case where the probability distribution is defined by crisp inequalities. We propose a chance constrained approach and a compromise programming approach to transform the multiobjective stochastic linear program with linear partial information on probability distribution into its equivalent uniobjective problem. The resulting program is then solved using the modified L-shaped method. We illustrate Our results by an example. (C) 2009 Elsevier B.V. All rights reserved.
Keywords:
Multiobjective stochastic programming
Compromise programming
Chance constrained approach
Modified L-shaped method
Journal
IF:
6
Papers:
2.2W
Citations:
6.4W