A non-dominated sorting hybrid algorithm for multi-objective optimization of engineering problems

被引：49

作者：

Ghiasi, Hossein ^{[1
]}

Pasini, Damiano ^{[1
]}

Lessard, Larry ^{[1
]}

机构：

[1] McGill Univ, Dept Mech Engn, Montreal, PQ H3A 2K6, Canada

来源：

ENGINEERING OPTIMIZATION | 2011年 / 43卷 / 01期

关键词：

multi-objective optimization; genetic algorithm; non-dominated sorting; hybrid algorithm; NSGA-II ALGORITHM; EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHM; MANUFACTURING OPTIMIZATION; SIMPLEX-METHOD;

D O I：

10.1080/03052151003739598

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Among numerous multi-objective optimization algorithms, the Elitist non-dominated sorting genetic algorithm (NSGA-II) is one of the most popular methods due to its simplicity, effectiveness and minimum involvement of the user. This article develops a multi-objective variation of the Nelder-Mead simplex method and combines it with NSGA-II in order to improve the quality and spread of the solutions. The proposed hybrid algorithm, called non-dominated sorting hybrid algorithm (NSHA), is compared with NSGA-II on several constrained and unconstrained test problems. The higher convergence rate and the wider spread of solutions obtained with NSHA make this algorithm a good candidate for engineering problems that require time-consuming simulation and analysis. To demonstrate this fact, NSHA is applied to the design of a carbon fibre bicycle stem simultaneously optimized for strength, weight and processing time.

引用

页码：39 / 59

页数：21

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