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

Document Type

Article

Publication Date

8-15-2019

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.

Identifier

85042173901 (Scopus)

Publication Title

Journal of Global Optimization

External Full Text Location

https://doi.org/10.1007/s10898-018-0622-5

e-ISSN

15732916

ISSN

09255001

First Page

599

Last Page

609

Issue

4

Volume

74

Grant

CMMI-1562466

Fund Ref

National Science Foundation

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