On the farther analysis of performance of the artificial searching swarm algorithm

Authors:
Tanggong Chen;Lijie Zhang;Lingling Pang
Affiliations:
Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin, China;Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin, China;Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin, China
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2010

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Adaptation in natural and artificial systems

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A Simulative Bionic Intelligent Optimization Algorithm: Artificial Searching Swarm Algorithm and Its Performance Analysis

CSO '09 Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization - Volume 02

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Abstract

Artificial Searching Swarm Algorithm (ASSA) is an intelligent optimization algorithm, and its performance has been analyzed and compared with some famous algorithms For farther understanding the running principle of ASSA, this work discusses the functions of three behavior rules which decide the moves of searching swarm Some typical functions are selected to do the simulation tests The function simulation tests showed that the three behavior rules are indispensability and endow the ASSA with powerful global optimization ability together.