Pareto optimality and particle swarm optimization

被引：106

作者：

Baumgartner, U ^{[1
]}

Magele, C ^{[1
]}

Renhart, W ^{[1
]}

机构：

[1] Graz Tech Univ, Inst Fundamentals & Theory Elect Engn, A-8010 Graz, Austria

来源：

IEEE TRANSACTIONS ON MAGNETICS | 2004年 / 40卷 / 02期

关键词：

pareto optimality; particle swarm optimization (PSO); stochastic optimization;

D O I：

10.1109/TMAG.2004.825430

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Real-world optimization problems often require the minimization/maximization of more than one objective, which, in general, conflict with each other. These problems (multiobjective optimization problems, vector optimization problems) are usually treated by using weighted sums or other decision-making schemes. An alternative way is to look for the pareto-optimal front. In this paper, the particle swarm algorithm is modified to detect the pareto-optimal front.

引用

页码：1172 / 1175

页数：4

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