Title :
Heterogeneous multi-processors scheduling by coevolutionary genetic algorithm
Author :
Zhong, Qiuxi ; Qi, Yue
Author_Institution :
Dept. of Comput. Sci., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
The efficacy and efficiency of conventional single population-based evolutionary algorithms (CEAs) decrease with the number of independent tasks in heterogeneous multi-processors systems. Based on computational model of cooperative coevolution, a task matching and scheduling algorithm is proposed for heterogeneous multi-processors systems, and the computation of individual´s fitness is given according to the cooperative interactions among species. Simulation results show that the coevolutionary genetic algorithm is more effective than CEA for multi-tasks matching and scheduling, and the algorithm is of practical use in engineering.
Keywords :
genetic algorithms; processor scheduling; CEA; coevolutionary GA; coevolutionary genetic algorithm; cooperative coevolution; cooperative interactions; evolutionary algorithms; heterogeneous multiprocessor scheduling; multitask matching; multitask scheduling; task matching algorithm; task scheduling algorithm; Automation; Computational modeling; Computer science; Evolutionary computation; Genetic algorithms; Genetic engineering; Processor scheduling; Programmable logic arrays; Scheduling algorithm; Workstations;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1021385
