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A Genetic Algorithm for Multiprocessor Scheduling
February 1994 (vol. 5 no. 2)
pp. 113-120

The problem of multiprocessor scheduling can be stated as finding a schedule for ageneral task graph to be executed on a multiprocessor system so that the schedulelength can be minimized. This scheduling problem is known to be NP-hard, and methodsbased on heuristic search have been proposed to obtain optimal and suboptimal solutions.Genetic algorithms have recently received much attention as a class of robust stochasticsearch algorithms for various optimization problems. In this paper, an efficient methodbased on genetic algorithms is developed to solve the multiprocessor scheduling problem.The representation of the search node is based on the order of the tasks being executedin each individual processor. The genetic operator proposed is based on the precedencerelations between the tasks in the task graph. Simulation results comparing the proposedgenetic algorithm, the list scheduling algorithm, and the optimal schedule using randomtask graphs, and a robot inverse dynamics computational task graph are presented.

[1] M. R. Garey and D. S. Johnson,Computers and Intractability: A Guide to Theory of NP-Completeness. San Francisco, CA: Freeman, 1979.
[2] C.V. Ramamoorthyet al., "Optimal scheduling strategies in a multiprocessor system,"IEEE Trans. Comput., vol. C-21, pp. 137-146, Feb. 1972.
[3] T. L. Adam, K. M. Chandy, and J. R. Dickson, "A comparison of list schedules for parallel processing systems,"Commun. ACM, vol. 17, no. 12, pp. 685-690, Dec. 1974.
[4] M. J. Gonzales, "Deterministic processor scheduling,"ACM Comput. Surveys, vol. 9, no. 3, Sept. 1977.
[5] H. Kasahara and S. Narita, "Practical multiprocessing scheduling algorithms for efficient parallel processing,"IEEE Trans. Comput., vol. C-33, no. 11, pp. 1023-1029, Nov. 1984.
[6] H. Kasahara and S. Narita, "Parallel Processing of Robot-Arm-Control Computation on a Multiprocessor System,"IEEE J. Robotics Automation, Vol. RA-1, No. 3, June 1985, pp. 104-113.
[7] C. L. Chen, C. S. Lee, E. S. H. Hou, "Efficient scheduling algorithm for robot inverse dynamics computation on a multiprocessor system,"IEEE Trans. Syst., Man, Cybern., vol. 18, no. 5, pp. 729-742, Sept. 1988.
[8] B. Hellstrom and L. Kanal, "Asymmetric mean-field neural networks for multiprocessor scheduling,"Neural Networks, vol. 5, pp. 671-686, 1992.
[9] Proc. 1st Int. Conf. Genetic Algorithms and Their Applications, July 24-26, 1985, Carnegie-Mellon University, Pittsburgh, PA.
[10] Proc. 2nd Int. Conf. Genetic Algorithms and Their Applications, July 28-31, 1987, MIT, Cambridge, MA,
[11] Proc. 3rd Int. Conf. Genetic Algorithms, June 4-7, 1989, George Mason Univ., Washington, DC.
[12] D. E. Goldberg,Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.
[13] J. H. Holland,Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press, 1975.
[14] L. Davis, "Job shop scheduling with genetic algorithms,"Proc. 1st Int. Conf. Genetic Algorithms and Their Applications, July 24-26, 1985, Carnegie-Mellon University, Pittsburgh, PA, pp. 136-140.
[15] K. Hwang and F. A. Briggs,Computer Architecture and Parallel Processing. New York: McGraw-Hill, 1984.
[16] N. Desni, "Generating random task graphs with known optimal schedule for multiprocessing scheduling," Master's Project Rep., NJIT, Newark, NJ, 1993.

Index Terms:
Index Termsgenetic algorithms; optimisation; computational complexity; multiprocessing systems;scheduling; performance evaluation; genetic algorithm; multiprocessor scheduling;NP-hard; heuristic search; robust stochastic search algorithms; optimization; simulation;list scheduling; random task graphs; robot inverse dynamics computational task graph
Citation:
E.S.H. Hou, N. Ansari, H. Ren, "A Genetic Algorithm for Multiprocessor Scheduling," IEEE Transactions on Parallel and Distributed Systems, vol. 5, no. 2, pp. 113-120, Feb. 1994, doi:10.1109/71.265940
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