Mega process genetic algorithm using grid MP

Authors:
Yoshiko Hanada;Tomoyuki Hiroyasu;Mitsunori Miki;Yuko Okamoto
Affiliations:
Graduate School, Department of Knowledge Engineering and Computer Sciences, Doshisha University, Kyoto, Japan;Department of Knowledge Engineering and Computer Sciences, Doshisha University, Kyoto, Japan;Department of Knowledge Engineering and Computer Sciences, Doshisha University, Kyoto, Japan;Department of Theoretical Studies, Institute for Molecular Science, Okazaki, Aichi, Japan
Venue:
LSGRID'04 Proceedings of the First international conference on Life Science Grid
Year:
2004

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Abstract

In this study, a new Genetic Algorithm (GA) using the Tabu · Local Search mechanism is proposed. The GA described in this paper is considered a Mega Process GA, which has an effective mechanism to use massive processors, i.e., Mega Processors, in large-scale computing systems. Our proposed method has a GA-specific database that possesses information of searched space and performs a local search for the space that is not searched. Such mechanisms enable us to comprehend the quantitative rate of a searched region during the search. Using this information, the searched space can be expanded linearly as the number of computing resources increases and the exhaustive search is guaranteed under infinite computations. The proposed GA was applied to numerical test functions and the energy minimization problems of protein tertiary structures. The latter problem was performed under a heterogeneous distributed computing environment, which was built up with Grid MP produced by United Devices Inc.