Space transformation search: a new evolutionary technique

Authors:
Hui Wang;Zhijian Wu;Yong Liu;Jing Wang;Dazhi Jiang;Lili Chen
Affiliations:
Wuhan University, Wuhan, China;Wuhan University, Wuhan, China;University of Aizu, Fukushima, Japan;Wuhan University, Wuhan, China;Wuhan University, Wuhan, China;Wuhan University, Wuhan, China
Venue:
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Year:
2009

Citing 5
Cited 8

Adaptation in natural and artificial systems

Adaptation in natural and artificial systems
Geographic Hypermedia using Search Space Transformation

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
No free lunch theorems for optimization

IEEE Transactions on Evolutionary Computation
Evolutionary programming made faster

IEEE Transactions on Evolutionary Computation
Opposition-Based Differential Evolution

IEEE Transactions on Evolutionary Computation

A Novel Evolutionary Algorithm Based on Multi-parent Crossover and Space Transformation Search

ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
Hybrid differential evolution algorithm with chaos and generalized opposition-based learning

ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
Enhancing particle swarm optimization using generalized opposition-based learning

Information Sciences: an International Journal
A hybrid parallel evolutionary algorithm based on elite-subspace strategy and space transformation search

HPCA'09 Proceedings of the Second international conference on High Performance Computing and Applications
A hybrid particle swarm optimization algorithm based on space transformation search and a modified velocity model

HPCA'09 Proceedings of the Second international conference on High Performance Computing and Applications
Generalised opposition-based differential evolution: an experimental study

International Journal of Computer Applications in Technology
An enhanced differential evolution algorithm for solving large scale optimisation problems on graphics hardware

International Journal of Computer Applications in Technology
Survey A review of opposition-based learning from 2005 to 2012

Engineering Applications of Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a new evolutionary technique is proposed, namely space transformation search (STS), which transforms current search space to a new search space. By simultaneously evaluating solutions in current search space and transformed space, we can provide more chances to find solutions more closely to the global optimum and finally accelerate convergence speed. The proposed STS method can be applied to many evolutionary algorithms, and this paper only presents a STS based particle swarm optimization (PSO-STS). Experimental studies on 20 benchmark functions including 10 shifted functions show that the PSO-STS and its variations can not only achieve better results, but also obtain faster convergence speed than the standard PSO.