Title

An incremental genetic algorithm approach to multiprocessor scheduling

Authors

Authors

A. S. Wu; H. Yu; S. Y. Jin; K. C. Lin;G. Schiavone

Comments

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Abbreviated Journal Title

IEEE Trans. Parallel Distrib. Syst.

Keywords

genetic algorithm; task scheduling; parallel processing; TASK DUPLICATION; GRAPHS; Computer Science, Theory & Methods; Engineering, Electrical & Electronic

Abstract

We have developed a genetic algorithm (GA) approach to the problem of task scheduling for multiprocessor systems. Our approach requires minimal problem specific information and no problem specific operators or repair mechanisms. Key features of our system include a flexible, adaptive problem representation and an incremental fitness function. Comparison with traditional scheduling methods indicates that the GA is competitive in terms of solution quality if it has sufficient resources to perform its search. Studies in a nonstationary environment show the GA is able to automatically adapt to changing targets.

Journal Title

Ieee Transactions on Parallel and Distributed Systems

Volume

15

Issue/Number

9

Publication Date

1-1-2004

Document Type

Article

Language

English

First Page

824

Last Page

834

WOS Identifier

WOS:000222679300005

ISSN

1045-9219

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