The computing of the optimal power consumption for semi-track air-cushion vehicle using hybrid generalized extremal optimization

被引：13

作者：

Xie, Dong ^{[1
]}

Luo, Zhe ^{[1
]}

Yu, Fan ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Automot Engn, Shanghai 200240, Peoples R China

来源：

APPLIED MATHEMATICAL MODELLING | 2009年 / 33卷 / 06期

关键词：

Semi-track air-cushion vehicle; Extremal optimization; Optimal design; Genetic algorithm; CRITICALITY; ALGORITHMS; OPERATORS; DESIGN; MODEL;

D O I：

10.1016/j.apm.2008.08.017

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A new stochastic method named hybrid generalized extremal optimization (HGEO) is proposed in this paper. It combines genetic algorithms (GAs) and generalized extremal optimization (GEO). In order to extend GEO's mutation operator to accelerate convergence speed and be easily incorporated into HGEO, the real coded GEO is first developed to population-base GEO (PGEO), and then incorporated into the HGEO in the paper. Constraints consideration for using the HGEO and the effects of related operators are also investigated. Finally, the performance of the HGEO is fully investigated compared with other related algorithms to find the optimal power consumption for the semi-track air-cushion vehicle (STACV). The results show that the HGEO has better performance than GAs or other related simpler algorithms. (C) 2008 Elsevier Inc. All rights reserved.

引用

页码：2831 / 2844

页数：14

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