Paper Info
Title
On the Convergence Properties of Quantum-Inspired Multi-Objective Evolutionary Algorithms
Abstract
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.
Year
DOI
Venue
2007
10.1007/978-3-540-74282-1_28
ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES
Keywords
Field
DocType
quantum computing,multi-objective evolutionary algorithms,Pareto optimal set,stochastic convergence
Convergence (routing),Evolutionary algorithm,Human-based evolutionary computation,Computer science,Quantum computer,Pareto optimal,Theoretical computer science,Artificial intelligence,Evolutionary programming,Quantum,Set theory,Mathematical optimization,Machine learning
Conference
Volume
ISSN
Citations 
2
1865-0929
5
PageRank 
References 
Authors
0.41
11
3
Name
Order
Citations
PageRank
Zhiyong Li150.41
Zhe Li250.41
Günter Rudolph321948.59