Review article

https://doi.org/10.31803/tg-20210901142449

A New "Intersection" Method for Multi-Objective Optimization in Material Selection

Maosheng Zheng orcid.org/0000-0003-3361-4060 ; School of Chemical Engineering, Northwest University, No. 229, Taibai North Road, Xi’an, 710069, Shaanxi Province, China
Yi Wang ; School of Chemical Engineering, Northwest University, No. 229, Taibai North Road, Xi’an, 710069, Shaanxi Province, China
Haipeng Teng ; School of Chemical Engineering, Northwest University, No. 229, Taibai North Road, Xi’an, 710069, Shaanxi Province, China

Abstract

Till now the previous methods for multi-objective optimization adopt the "additive" algorithm for the normalized evaluation indexes, which has the inherent shortcoming of taking the form of "union" in the viewpoint of set theory. In fact, "simultaneous optimization of multiple indexes" should be more appropriate to take the form of "intersection" for the normalized evaluation indexes in the respects of set theory and "joint probability" in probability theory. In this paper, a new concept of favorable probability is proposed to reflect the favorable degree of the candidate material in the selection; All material property indicators are divided into beneficial or unbeneficial types to the material selection; Each material property indicator correlates to a partial favorable probability quantitatively, and the total favorable probability of a candidate material is the product of all partial favorable probabilities in the viewpoints of "intersection" of set theory and "joint probability" in probability theory, which is the sole decisive index in the competitive selection process. Results of the application examples indicate the validity of the new method.

Keywords

favorable probability; material selection; multi-objective optimization; probability theory; quantitative assessment

Hrčak ID:

265009

URI

https://hrcak.srce.hr/265009

Publication date:

1.11.2021.

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