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Efficient solution concepts and their application in uncertain multiobjective programming
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DOI：10.1016/j.asoc.2016.07.021.png)
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Abstract
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Based on uncertainty theory, we investigate the relations among efficiency concepts of the multiobjective programming (MOP) with uncertain vectors. We first propose the uncertain MOP model, and study its convexity. Then, we define different efficiency concepts such as expected-value efficiency, expected-value proper efficiency, and establish their relations under the assumed conditions, which are illustrated through two numerical examples. Finally, in the uncertain environment, we apply the theoretical results to a redundancy allocation problem with two objective in reparable parallel-series systems, and discuss how to obtain different types of efficient solutions according to the decision-maker's preferences. (C) 2016 Elsevier B.V. All rights reserved.
Keywords:
Uncertainty theory
Uncertain multiobjective programming
Pareto efficiency
Redundancy allocation problema
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