Imperialist Competitive Algorithms with Perturbed Moves for Global Optimization

Jun Lin Lin; Chun Wei Cho; Hung Chjh Chuan

doi:10.4028/www.scientific.net/AMM.284-287.3135

Paper Titles

High Resolution Time-Frequency Analysis Base on Ricker Atom Matching Pursuit Decomposition
p.3115

Human Body and Body Part Movement Analysis Using Gyroscope, Accelerometer and Compass
p.3120

Human Hand Movement Analysis Using Principle Component Analysis Classifier
p.3126

Image Segmentation Based on Poisson Equation
p.3131

Imperialist Competitive Algorithms with Perturbed Moves for Global Optimization
p.3135

Unsupervised Mining of Visually and Temporally Consistent Shots for Sports Video Summarization
p.3140

Theoretical Approach to Reduced Q-Matrix for Cognition Diagnosis
p.3145

Solve the Routing Optimization Problems with Foraging Game Theory
p.3149

Significant Features Selection Resistant to Temporal Distortions
p.3154

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 284-287Imperialist Competitive Algorithms with Perturbed...

Imperialist Competitive Algorithms with Perturbed Moves for Global Optimization

Abstract:

Imperialist Competitive Algorithm (ICA) is a new population-based evolutionary algorithm. Previous works have shown that ICA converges quickly but often to a local optimum. To overcome this problem, this work proposed two modifications to ICA: perturbed assimilation move and boundary bouncing. The proposed modifications were applied to ICA and tested using six well-known benchmark functions with 30 dimensions. The experimental results indicate that these two modifications significantly improve the performance of ICA on all six benchmark functions.