Title :
Efficient multiprocessor scheduling based on genetic algorithms
Author :
Hou, E.S.H. ; Hong, R. ; Ansari, N.
Author_Institution :
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
An efficient method, based on genetic algorithms, for solving the multiprocessor scheduling problem is proposed. The representation of the search node is based on the schedule of the tasks in each individual processor. The genetic operator is based on the precedence relations between the tasks in the task graph. The genetic algorithm is applied to the problem of scheduling robot inverse dynamics computations
Keywords :
genetic algorithms; multiprocessing systems; scheduling; genetic algorithms; multiprocessor scheduling; operator; precedence relations; robot inverse dynamics computations; Computational complexity; Concurrent computing; Genetic algorithms; Multiprocessing systems; Processor scheduling; Robots; Robustness; Scheduling algorithm; Stochastic processes; Topology;
Conference_Titel :
Industrial Electronics Society, 1990. IECON '90., 16th Annual Conference of IEEE
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-87942-600-4
DOI :
10.1109/IECON.1990.149314
