摘要
在协同设计子任务间形成的任务前趋图的基础上,面向协同设计的实际需求,采用了两个任务调度算法:改进的AGA(Adaptive Genetic Algorithm,自适应遗传算法)及GASA(Genetic Simulated Annealing Algorithm,遗传-模拟退火算法)。分别给出了算法的详细实现,分析并比较了算法与其它任务调度算法的效能。最后,针对较大规模的任务实例对这两个算法进行了横向比较,分析了它们的时间效率和适用场合。
A reasonable task scheduling algorithm can effectively improve the quality and efficiency of Collaborative Design. For the actual demand of Collaborative Design, two task scheduling algorithms are adopted based on the task precedence graph formed by subtasks. One is improved Adaptive Genetic Algorithm, the other is Genetic Simulated Annealing Algorithm. The detailed steps are given, the performance of the algorithms are also analyzed with comparison with other task scheduling algorithm. Finally, these two algorithms are compared horizontally for relatively large-scale examples, and the time efficiency and application occasions are analyzed as well.
出处
《中山大学学报（自然科学版）》
CAS
CSCD
北大核心
2008年第6期104-108,共5页
Acta Scientiarum Naturalium Universitatis Sunyatseni
基金
国家自然科学基金资助项目(60573174)
国家自然科学基金资助项目(60673028)
