A Reliable Parallel Interval Global Optimization Algorithm Based on Mind Evolutionary Computation

Author

Lei, Yongmei ; Chen, Shaojun

Author_Institution

Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China

fYear

2009

fDate

21-22 Aug. 2009

Firstpage

205

Lastpage

209

Abstract

In this paper, we investigate the parallel reliable computational model and propose a parallel interval evolutionary algorithm that integrates interval arithmetic and Mind Evolutionary Computation method. The major aim is to explorer the new parallel interval decomposition scheme can solve computation intensive problem and can determine the all optimal solution reliably. The proposed algorithm is experimentally testified on the ZiQiang 3000 cluster of Shanghai High Education Grid-e-Grid Computational Application Platform with a test suit containing 6 complex multi-modal function optimization benchmarks.

Keywords

evolutionary computation; grid computing; optimisation; parallel algorithms; software reliability; Shanghai High Education Grid-e-Grid Computational Application Platform; ZiQiang 3000 cluster; computation intensive problem; evolutionary algorithm; global optimization algorithm; interval arithmetic; mind evolutionary computation; multimodal function optimization benchmarks; parallel interval decomposition scheme; parallel reliable computational model; Acceleration; Algorithm design and analysis; Clustering algorithms; Concurrent computing; Evolutionary computation; Grid computing; Optimization methods; Parallel algorithms; Reliability engineering; Testing; Interval algorithm; Parallel reliable computing; global optimization; mind evolutionary computation;

fLanguage

English

Publisher

ieee

Conference_Titel

ChinaGrid Annual Conference, 2009. ChinaGrid '09. Fourth

Conference_Location

Yantai, Shandong

Print_ISBN

978-0-7695-3818-1

Type

conf

DOI

10.1109/ChinaGrid.2009.29

Filename

5328922