On Two Approaches to Constructing Optimal Algorithms for Multi-objective Optimization
Multi-objective optimization problems with expensive, black box objectives are difficult to tackle. For such type of problems in the single objective case the algorithms, which are in some sense optimal, have proved well suitable. Two concepts of optimality substantiate the construction of algorithms: worst case optimality and average case optimality. In the present paper the extension of these concepts to the multi-objective optimization is discussed. Two algorithms representing both concepts are implemented and experimentally compared.
KeywordsMulti-objective optimization global optimization optimal algorithms statistical models
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