A Hierarchical Approach in Distributed Evolutionary Algorithms for Multiobjective Optimization

Authors:
Daniela Zaharie;Dana Petcu;Silviu Panica
Affiliations:
Department of Computer Science, West University of Timişoara, and Institute e-Austria Timişoara, Timişoara, Romania 300223;Department of Computer Science, West University of Timişoara, and Institute e-Austria Timişoara, Timişoara, Romania 300223;Department of Computer Science, West University of Timişoara, and Institute e-Austria Timişoara, Timişoara, Romania 300223
Venue:
Large-Scale Scientific Computing
Year:
2009

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Abstract

This paper presents a hierarchical and easy configurable framework for the implementation of distributed evolutionary algorithms for multiobjective optimization problems. The proposed approach is based on a layered structure corresponding to different execution environments like single computers, computing clusters and grid infrastructures. Two case studies, one based on a classical test suite in multiobjective optimization and one based on a data mining task, are presented and the results obtained both on a local cluster of computers and in a grid environment illustrates the characteristics of the proposed implementation framework.