An incremental genetic algorithm approach to multiprocessor scheduling 论文

2004IEEE Transactions on Parallel and Distributed Systems引用 251
Distributed and Parallel Computing SystemsScheduling and Optimization AlgorithmsParallel Computing and Optimization Techniques

详细信息

发表期刊/会议
IEEE Transactions on Parallel and Distributed Systems
发表日期
2004-09-01
发表年份
2004

关键词

Distributed and Parallel Computing SystemsScheduling and Optimization AlgorithmsParallel Computing and Optimization Techniques

摘要

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.