An interactive surrogate-based method for computationally expensive multiobjective optimisation

被引：8

作者：

Tabatabaei, Mohammad ^{[1
]}

Hartikainen, Markus ^{[1
]}

Sindhya, Karthik ^{[1
]}

Hakanen, Jussi ^{[1
]}

Miettinen, Kaisa ^{[1
]}

机构：

[1] Univ Jyvaskyla, Fac Informat Technol, Jyvaskyla, Finland

来源：

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY | 2019年 / 70卷 / 06期

基金：

芬兰科学院;

关键词：

Multiple criteria decision-making (MCDM); interactive methods; computational cost; black-box functions; metamodeling techniques; achievement scalarising function; INTERPOLATION; ALGORITHMS; METAMODEL; SURFACE; MODELS;

D O I：

10.1080/01605682.2018.1468860

中图分类号：

C93 [管理学];

学科分类号：

12 ; 1201 ; 1202 ; 120202 ;

摘要：

Many disciplines involve computationally expensive multiobjective optimisation problems. Surrogate-based methods are commonly used in the literature to alleviate the computational cost. In this paper, we develop an interactive surrogate-based method called SURROGATE-ASF to solve computationally expensive multiobjective optimisation problems. This method employs preference information of a decision-maker. Numerical results demonstrate that SURROGATE-ASF efficiently provides preferred solutions for a decision-maker. It can handle different types of problems involving for example multimodal objective functions and nonconvex and/or disconnected Pareto frontiers.

引用

页码：898 / 914

页数：17

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