A Self-Adaptive Genetic Algorithm for Tasks Scheduling in Multiprocessor System

摘要：

Task scheduling is one of the crucial issues to achieve high performance for parallel multiprocessor systems. With the extensive studies of the task scheduling problem, many new methods, especial genetic algorithms, have been introduced into this field. In this paper, we develop a novel genetic algorithm, namely the self-adaptive genetic algorithm (SAGA). SAGA is different from the previously proposed genetic algorithms in a number of ways. Unlike the other genetic algorithms, SAGA makes some key parameters changeable with variable policy over the evolution. SAGA also efficiently generates the initial population, which may contain any possible feasible solutions. Simulation results show that SAGA outperforms the previously proposed algorithms in terms of the solution quality.

作者: Lan Zhou Sun Shi-Xin

作者单位: College of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu, Sichuan 610054, China

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 2098-2101

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）