Sciweavers

Share
CEC
2010
IEEE

A mixed strategy for Evolutionary Programming based on local fitness landscape

9 years 2 months ago
A mixed strategy for Evolutionary Programming based on local fitness landscape
The performance of Evolutionary Programming (EP) is affected by many factors (e.g. mutation operators and selection strategies). Although the conventional approach with Gaussian mutation operator may be efficient, the initial scale of the whole population can be very large. This may lead to the conventional EP taking too long to reach convergence. To combat this problem, EP has been modified in various ways. In particular, modifications of the mutation operator may significantly improve the performance of EP. However, operators are only efficient within certain fitness landscapes. The mixed strategies have therefore been proposed in order to combine the advantages of different operators. The design of a mixed strategy is currently based on the performance of applying individual operators. Little is directly relevant to the information of local fitness landscapes. This paper presents a modified mixed strategy, which automatically adapts to local fitness landscapes, and implements a trai...
Liang Shen, Jun He
Added 08 Nov 2010
Updated 08 Nov 2010
Type Conference
Year 2010
Where CEC
Authors Liang Shen, Jun He
Comments (0)
books