Conference Paper

A Scalability Test for Accelerated DE Using Generalized Opposition-Based Learning

State Key Lab. of Software Eng., Wuhan Univ., Wuhan, China
DOI: 10.1109/ISDA.2009.216 Conference: Ninth International Conference on Intelligent Systems Design and Applications, ISDA 2009, Pisa, Italy , November 30-December 2, 2009
Source: IEEE Xplore

ABSTRACT In this paper a scalability test over eleven scalable benchmark functions, provided by the current workshop (Evolutionary Algorithms and other Metaheuristics for Continuous Optimization Problems-A Scalability Test), are conducted for accelerated DE using generalized opposition-based learning (GODE). The average error of the best individual in the population has been reported for dimensions 50, 100, 200, and 500 in order to compare with the results of other algorithms which are participating in this workshop. Current work is based on opposition-based differential evolution (ODE) and our previous work, accelerated PSO by generalized OBL.

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