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A Simple But Effective Evolutionary Algorithm for Complicated Optimization Problems

Author(s)
Xu, Y.G.; Liu, Guirong
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Abstract
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.
Date issued
2002-01
URI
http://hdl.handle.net/1721.1/4012
Series/Report no.
High Performance Computation for Engineered Systems (HPCES);
Keywords
evolutionary algorithm, optimization

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