A Java-based parallel platform for the implementation of evolutionary computation for engineering applications

Authors:
Chun Che Fung;Jia Bin Li;Kok Wai Wong;Kit Po Wang
Affiliations:
School of Information Technology, Murdoch University, Murdoch, W.A., Australia;School of Information Technology, Murdoch University, Murdoch, W.A., Australia;School of Computer Engineering, Nanyang Technological University, Singapore;Department of Electrical Engineering, Hong Kong Polytechnic University, Hong Kong SAR
Venue:
International Journal of Systems Science
Year:
2004

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Abstract

As computers continually improve in performance and decrease in manufacturing cost, distributed systems consisting of multiple computers implemented as parallel computation platforms have become viable for engineering applications which demand intensive computation power. This paper proposes an extended version of a previously developed low cost parallel computation platform called para worker. The system is based on a cluster structure which is a form of a distributed system. The new system is termed para worker 2 which differentiates it from the earlier system. The new proposed system adds enhanced features of improved dynamic object reallocation, adaptive consistency protocols, and location transparency. Performance of the para worker 2 has proven to be superior to the para worker. Testing was based on an execution of Genetic Algorithm to solve the Economic Dispatch problem in Power Engineering. The proposal is particularly useful for the implementation and execution of computational intelligence techniques such as evolutionary computing for engineering applications.