On the Statistical Models-Based Multi-objective Optimization

Antanas Žilinskas ()
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Antanas Žilinskas: Vilnius University, Institute of Mathematics and Informatics

A chapter in Optimization in Science and Engineering, 2014, pp 597-610 from Springer

Abstract: Abstract Multi-objective optimization problems with expensive, black-box objectives are difficult to tackle. For such type of single-objective global optimization problems, the algorithms based on the statistical models of objective functions and the concept of rational decision theory are well suitable. In the present paper that approach to constructing of single-objective algorithms is generalized and extended to multi-objective optimization. An algorithm, based on the proposed approach, is implemented. Several numerical examples are presented to illustrate the performance of the implemented algorithm.

Keywords: Objective Function; Global Optimization; Generational Distance; Global Optimization Algorithm; Nondominated Solution (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4939-0808-0_29

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DOI: 10.1007/978-1-4939-0808-0_29

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