Free search of global value

Author

Vasileva, Vesela ; Penev, Kalin

Author_Institution

Technol. Sch., Southampton Solent Univ., Southampton, UK

fYear

2012

fDate

6-8 Sept. 2012

Firstpage

425

Lastpage

430

Abstract

This article presents a novel investigation on two real value methods Free Search and Particle Swarm Optimization applied to global optimization numerical tests. The objective is to identify how to facilitate assessment of heuristic, evolutionary, adaptive and other optimization and search algorithms. Particular aim is to measure: (1) probability for success of given method; (2) abilities of given method for entire search space coverage; (3) dependence on initialization; (4) abilities of given method to escape from trapping in local sub-optima. Achieved experimental results are presented and analyzed.

Keywords

evolutionary computation; particle swarm optimisation; probability; search problems; adaptive algorithm; evolutionary algorithm; global optimization numerical test; global value free search; heuristic algorithm; initialization dependence; local suboptima trapping; particle swarm optimization; real value method; search algorithm assessment; search space coverage; success probability; Charge carrier processes; Convergence; Linear programming; Optimization; Particle swarm optimization; Search problems; Sociology; Free Search; Global Optimization; Heuristic Methods; Numerical Tests; Particle Swarm Optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (IS), 2012 6th IEEE International Conference

Conference_Location

Sofia

Print_ISBN

978-1-4673-2276-8

Type

conf

DOI

10.1109/IS.2012.6335172

Filename

6335172