Dynamic Sequencing of A Multi-Processor System: A Genetic Algorithm Approach
The dynamic sequencing of jobs through a multiprocessor system is one to which little attention has been paid, in contrast to the extensive literature on static sequencing problems. Yet in many real problems, to assume, as the static model does, that we know about all jobs that will arrive in the course of a processing cycle is hardly realistic.
Existing solutions usually assume a queueingtheoretic orientation, rather than an optimization one, in which the decision as to which job should be processed is made on the basis of some simple selection criteria, such as First-Come First-Served, or Shortest Processing Time.
Here we investigate the use of a Genetic Algorithm (GA) to solve the successive sequencing problems generated by finding a near-optimal sequence for those jobs available just before successive event times—the times at which the job being processed on the first processor completes its processing. Some comparisons are made between using the GA approach versus some simple rules.
KeywordsGenetic Algorithm Multiprocessor System Throughput Rate Genetic Algorithm Approach Dynamic Sequencing
Unable to display preview. Download preview PDF.
- G.A. Cleveland and S.F. Smith (1989) Using genetic algorithms to schedule flow shop releases. In J.D. Schaffer (Ed.) (1989) Proceedings of the 3rd International Conference on Genetic Algorithms. Morgan Kaufmann, Los Altos, CA.Google Scholar
- H.M. Cartwright and G.F. Mott (1991) Looking around: using clues from the data space to guide genetic algorithm searches. In R.K. Belew and L.B. Booker (Eds.) (1991) Proceedings of the 4th International Conference on Genetic Algorithms. Morgan Kaufmann, San Mateo, CA.Google Scholar
- C.R. Reeves (1993) A genetic algorithm for flowshop sequencing. Computers & Ops. Res., (in review).Google Scholar
- C.R. Reeves (1992) A genetic algorithm approach to stochastic flowshop sequencing. Proc. IEE Colloquium on Genetic Algorithms for Control and Systems Engineering. Digest No.1992/106, IEE, London.Google Scholar
- R.W. Conway, W.L. Maxwell and L.W. Miller (1967) Theory of Scheduling. Addison-Wesley, Reading, Mass.Google Scholar
- C.H. Sauer and K.M. Chandy (1981) Computer Systems Performance Modelling. Prentice-Hall, New Jersey.Google Scholar