DynDE : a differential evolution for dynamic optimization problems

This paper presents an approach of using Differential Evolution (DE) to solve dynamic optimization problems. Careful setting of parameters is necessary for DE algorithms to successfully solve optimization problems. This paper describes DynDE, a multi-population DE algorithm developed specifically to...

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Bibliographic Details
Main Author: Mendes, Rui (author)
Other Authors: Mohais, Arvind (author)
Format: conferencePaper
Language:eng
Published: 2005
Subjects:
Dynamic optimization
Differential evolution
Science & Technology
Online Access:http://hdl.handle.net/1822/3093
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/3093
Description
Summary:This paper presents an approach of using Differential Evolution (DE) to solve dynamic optimization problems. Careful setting of parameters is necessary for DE algorithms to successfully solve optimization problems. This paper describes DynDE, a multi-population DE algorithm developed specifically to solve dynamic optimization problems that doesn't need any parameter control strategy for the F or CR parameters. Experimental evidence has been gathered to show that this new algorithm is capable of efficiently solving the moving peaks benchmark.

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