Multi-objective structural optimization base on improved NSGA-II algorithm

M. Z. Lai; Z. M. Duan; G. Y. Zhang; B. D

doi:10.3923/itj.2013.7646.7650

Multi-objective structural optimization base on improved NSGA-II algorithm

M. Z. Lai^*
, Z. M. Duan
, G. Y. Zhang
, B. D

^*Corresponding author for this work

Harbin University of Science and Technology
HLJ Province Electronic and Information Products Supervision Inspection Institute
School of Astronautics, Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

A kind of fast and elitist multi-objective genetic algorithm (nondominated sorting genetic algorithm-II) was presented to solve high dimension and multi-modal optimal problems. T His fuzzy information could be converted into a mathematically well-structured problem based on fuzzy optimal theory. And the improved crossover operator of NSGA-II was applied to obtain the optimal solution. According to the test results on a typical test function and an application on the structural fuzzy multi-objective optimization of three-bar truss, more reasonable distributed solutions could be obtained and the diversity of the solutions could be maintained. It provides beneficial references for engineering application of fuzzy multi-objective structure optimization.

Original language	English
Pages (from-to)	7646-7650
Number of pages	5
Journal	Information Technology Journal
Volume	12
Issue number	23
DOIs	https://doi.org/10.3923/itj.2013.7646.7650
State	Published - 2013
Externally published	Yes

Keywords

Fuzzy multi-objective
Nondominated sorting genetic algorithm-II (NSGA-II)
Structural optimization

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10.3923/itj.2013.7646.7650

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title = "Multi-objective structural optimization base on improved NSGA-II algorithm",

abstract = "A kind of fast and elitist multi-objective genetic algorithm (nondominated sorting genetic algorithm-II) was presented to solve high dimension and multi-modal optimal problems. T His fuzzy information could be converted into a mathematically well-structured problem based on fuzzy optimal theory. And the improved crossover operator of NSGA-II was applied to obtain the optimal solution. According to the test results on a typical test function and an application on the structural fuzzy multi-objective optimization of three-bar truss, more reasonable distributed solutions could be obtained and the diversity of the solutions could be maintained. It provides beneficial references for engineering application of fuzzy multi-objective structure optimization.",

keywords = "Fuzzy multi-objective, Nondominated sorting genetic algorithm-II (NSGA-II), Structural optimization",

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year = "2013",

doi = "10.3923/itj.2013.7646.7650",

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T1 - Multi-objective structural optimization base on improved NSGA-II algorithm

AU - Lai, M. Z.

AU - Duan, Z. M.

AU - Zhang, G. Y.

AU - D, B.

PY - 2013

Y1 - 2013

N2 - A kind of fast and elitist multi-objective genetic algorithm (nondominated sorting genetic algorithm-II) was presented to solve high dimension and multi-modal optimal problems. T His fuzzy information could be converted into a mathematically well-structured problem based on fuzzy optimal theory. And the improved crossover operator of NSGA-II was applied to obtain the optimal solution. According to the test results on a typical test function and an application on the structural fuzzy multi-objective optimization of three-bar truss, more reasonable distributed solutions could be obtained and the diversity of the solutions could be maintained. It provides beneficial references for engineering application of fuzzy multi-objective structure optimization.

AB - A kind of fast and elitist multi-objective genetic algorithm (nondominated sorting genetic algorithm-II) was presented to solve high dimension and multi-modal optimal problems. T His fuzzy information could be converted into a mathematically well-structured problem based on fuzzy optimal theory. And the improved crossover operator of NSGA-II was applied to obtain the optimal solution. According to the test results on a typical test function and an application on the structural fuzzy multi-objective optimization of three-bar truss, more reasonable distributed solutions could be obtained and the diversity of the solutions could be maintained. It provides beneficial references for engineering application of fuzzy multi-objective structure optimization.

KW - Fuzzy multi-objective

KW - Nondominated sorting genetic algorithm-II (NSGA-II)

KW - Structural optimization

UR - https://www.scopus.com/pages/publications/84901804355

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DO - 10.3923/itj.2013.7646.7650

M3 - 文章

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VL - 12

SP - 7646

EP - 7650

JO - Information Technology Journal

JF - Information Technology Journal

IS - 23

ER -

Multi-objective structural optimization base on improved NSGA-II algorithm

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Keywords

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