A Multi-objective Optimization Evolutionary Algorithm Addressing Diversity Maintenance

Author

Shen, Xiaoning ; Zhang, Min ; Li, Tao

Author_Institution

Sch. of Inf. & Control, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China

Volume

1

fYear

2009

fDate

24-26 April 2009

Firstpage

524

Lastpage

527

Abstract

A multi-objective evolutionary algorithm keeping diversity of the population is proposed. The algorithm makes use of a metric based on entropy to measure the diversity of the population. The evolving state of the current population is associated with the running mechanism of the algorithm by the diversity metric, and several strategies are designed to enhance the extent of exploration of the algorithm. Simulation results indicate that the proposed algorithm has good performance of convergence and distribution.

Keywords

entropy; evolutionary computation; optimisation; diversity maintenance; entropy; multiobjective optimization evolutionary algorithm; simulation result; Algorithm design and analysis; Approximation algorithms; Blindness; Character generation; Convergence; Diversity methods; Entropy; Evolutionary computation; Information science; Nearest neighbor searches; diversity; evolutionary algorithm; multi-objective optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on

Conference_Location

Sanya, Hainan

Print_ISBN

978-0-7695-3605-7

Type

conf

DOI

10.1109/CSO.2009.28

Filename

5193751