DocumentCode
3300358
Title
A novel self-organizing quantum evolutionary algorithm for multi-objective optimization
Author
Si, Lingling ; Shi, Leina ; Wang, Yanan
Author_Institution
HanDan Coll., Handan, China
fYear
2010
fDate
25-27 June 2010
Firstpage
499
Lastpage
503
Abstract
In this study, a self-organizing quantum evolutionary algorithm for multi-objective optimization (MSQEA) is proposed. Because of the quantum dynamic mechanism all the subpopulations may move concurrently in a force-field until all of them reach their equilibrium states. We estimate the performance of algorithm. The efficiency of the approach has been illustrated by applying to 0/1 Multi-objective knapsack problems. The results show that MSQEA can yield improvement in solution quality.
Keywords
Algorithm design and analysis; Chaos; Concurrent computing; Convergence; Educational institutions; Educational technology; Evolutionary computation; Parallel processing; Performance analysis; Quantum computing; Dynamic Mechanism; Multi-objective Optimization; Quantum Evolutionary Algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Educational and Network Technology (ICENT), 2010 International Conference on
Conference_Location
Qinhuangdao, China
Print_ISBN
978-1-4244-7660-2
Electronic_ISBN
978-1-4244-7662-6
Type
conf
DOI
10.1109/ICENT.2010.5532255
Filename
5532255
Link To Document