On the convergence properties of quantum-inspired multi-objective evolutionary algorithms

被引：0

作者：

Li, Zhiyong ^{[1
]}

Li, Zhe ^{[1
]}

Rudolph, Guenter ^{[2
]}

机构：

[1] Hunan Univ, Sch Comp & Commun, Changsha 410082, Hunan, Peoples R China

[2] Univ Dortmund, Fachbereich Informat, D-44221 Dortmund, Germany

来源：

ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES | 2007年 / 2卷

关键词：

quantum computing; multi-objective evolutionary algorithms; Pareto optimal set; stochastic convergence;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a general framework of quantum-inspired multiobjective evolutionary algorithms is proposed based on the basic principles of quantum computing and general schemes of multi-objective evolutionary algorithms. One of the sufficient convergence conditions to Pareto optimal set is presented and proved under partially order set theory. Moreover, two improved Q-gates are given as examples meeting this convergence condition.

引用

页码：245 / +

页数：2

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