A hierarchical approach in distributed evolutionary algorithms for multiobjective optimization

被引：6

作者：

Zaharie, Daniela ^{[1
]}

Petcu, Dana ^{[1
]}

Panica, Silviu ^{[1
]}

机构：

[1] W Univ Timisoara, Dept Comp Sci, Timisoara 300223, Romania

来源：

LARGE-SCALE SCIENTIFIC COMPUTING | 2008年 / 4818卷

关键词：

D O I：

10.1007/978-3-540-78827-0_59

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：516 / 523

页数：8

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