A Simple But Effective Evolutionary Algorithm for Complicated Optimization Problems

A simple but effective evolutionary algorithm is proposed in this paper for solving complicated optimization problems. The new algorithm presents two hybridization operations incorporated with the conventional genetic algorithm. It takes only 4.1% ~ 4.7% number of function evaluations required by th...

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Bibliographic Details
Main Authors: Xu, Y.G., Liu, Guirong
Format: Article
Language:en_US
Published: 2003
Subjects:
Online Access:http://hdl.handle.net/1721.1/4012
Description
Summary:A simple but effective evolutionary algorithm is proposed in this paper for solving complicated optimization problems. The new algorithm presents two hybridization operations incorporated with the conventional genetic algorithm. It takes only 4.1% ~ 4.7% number of function evaluations required by the conventional genetic algorithm to obtain global optima for the benchmark functions tested. Application example is also provided to demonstrate its effectiveness.