Abstract
We consider multiobjective optimization problems in which objective functions are in the form of mathematical expectation of functions depending on a random element and a constraints set can depend on a probability measure. An efficient points set characterizes the multiobjective problems very often instead of the solution set in one objective case. A stability of the efficient points set (w.r.t. a probability measures space) and empirical estimates have been already investigated in the case when all objective functions were assumed to be strongly convex. The aim of the contribution is to present a modified assertions under rather weaker assumptions.
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Kaňková, V. (2005). A Note on the Relationship between Strongly Convex Functions and Multiobjective Stochastic Programming Problems. In: Fleuren, H., den Hertog, D., Kort, P. (eds) Operations Research Proceedings 2004. Operations Research Proceedings, vol 2004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27679-3_38
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DOI: https://doi.org/10.1007/3-540-27679-3_38
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