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Utilizing the Correlation Between Constraints and Objective Function for Constrained Evolutionary Optimization

When solving constrained optimization problems by evolutionary algorithms, the core issue is to balance constraints and objective function. This paper is the first attempt to utilize the correlation between constraints and objective function to keep this balance. First of all, the correlation between constraints and objective function is mined and represented by a correlation index. Afterward, a weighted sum updating approach and an archiving and replacement mechanism are proposed to make use of this correlation index to guide the evolution. By the above process, a novel constrained optimization evolutionary algorithm is presented. Experiments on a broad range of benchmark test functions indicate that the proposed method shows better or at least competitive performance against other state-of-the-art methods. Moreover, the proposed method is applied to the gait optimization of humanoid robots.

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Informasi Detail

Judul Seri

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION; Vol.24 No.1 February 2020

No. Panggil

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Penerbit

: .,

Deskripsi Fisik

p. 29 - 43

Bahasa

English

ISBN/ISSN

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Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

-

Edisi

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Subjek

CONSTRAINTS
CORRELATION
OBJECTIVE FUNCTION
CONSTRAINED OPTIMIZATION
EVOLUTIONARY ALGORITHMS (EAS)
HUMANOID ROBOTS

Info Detail Spesifik

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Pernyataan Tanggungjawab

Yong Wang, Jia-Peng Li, Xihui Xue, Bing-chuan Wang

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