Title

An Incremental Genetic Algorithm Approach To Multiprocessor Scheduling

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. © 2004 IEEE.

Publication Date

9-1-2004

Publication Title

IEEE Transactions on Parallel and Distributed Systems

Volume

15

Issue

9

Number of Pages

824-834

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/TPDS.2004.38

Socpus ID

4544231492 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/4544231492

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