Bi-objective decision making in global optimization based on statistical models

Antanas Žilinskas () and James Calvin ()
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Antanas Žilinskas: Vilnius University
James Calvin: New Jersey Institute of Technology

Journal of Global Optimization, 2019, vol. 74, issue 4, No 2, 599-609

Abstract: Abstract A global optimization problem is considered where the objective functions are assumed “black box” and “expensive”. An algorithm is theoretically substantiated using a statistical model of objective functions and the theory of rational decision making under uncertainty. The search process is defined as a sequence of bi-objective selections of sites for the computation of the objective function values. It is shown that two well known (the maximum average improvement, and the maximum improvement probability) algorithms are special cases of the proposed general approach.

Keywords: Global optimization; Statistical models; Kriging; Bi-objective decision making; Rational decision making under uncertainty (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s10898-018-0622-5

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