Swarm intelligence for mixed-variable design optimization

被引：33

作者：

Guo C.-X. ^{[1
]}

Hu J.-S. ^{[1
]}

Ye B. ^{[1
]}

Cao Y.-J. ^{[1
]}

机构：

[1] Coll. of Elec. Eng., Zhejiang Univ.

来源：

Journal of Zhejiang University: Science | 2004年 / 5卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Engineering design optimization; Global optimization; Mixed variables; Swarm intelligence;

D O I：

10.1631/jzus.2004.0851

中图分类号：

学科分类号：

摘要：

Many engineering optimization problems frequently encounter continuous variables and discrete variables which add considerably to the solution complexity. Very few of the existing methods can yield a globally optimal solution when the objective functions are non-convex and non-differentiable. This paper presents a hybrid swarm intelligence approach (HSIA) for solving these nonlinear optimization problems which contain integer, discrete, zero-one and continuous variables. HSIA provides an improvement in global search reliability in a mixed-variable space and converges steadily to a good solution. An approach to handle various kinds of variables and constraints is discussed. Comparison testing of several examples of mixed-variable optimization problems in the literature shows that the proposed approach is superior to current methods for finding the best solution, in terms of both solution quality and algorithm robustness.

引用

页码：851 / 860

页数：9

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