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多处理机调度问题的蚁群优化算法 被引量:3

Multiprocessor Scheduling Based on Ant Colony Optimization Algorithm
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摘要 传统蚁群算法存在收敛速度慢、计算时间长、易陷入局部最优解等方面的缺陷。通过对蚁群信息素更新、策略选择、参数选择等各方面进行改进,提出一种更加高效的多处理机调度蚁群优化算法。实验证明:与其他优化算法相比,该算法能在较短的时间内找到更好的调度策略,具有较好的收敛性和有效性及优良的全局优化性能。 Traditional ant colony algorithm is improved to overcome the limitation of stagnation,slow rate of convergence and long time of computing.A more efficient ant colony optimization algorithm is proposed with multiprocessor scheduling.The algorithm improves ant colony pheromone updates,strategic selection,parameter selection and so forth.Better scheduling strategy is found in short time,with excellent global optimization properties.Simulation results show that this algorithm has better convergence and effective comparison than other optimization algorithms.
出处 《桂林理工大学学报》 CAS 北大核心 2013年第2期329-332,共4页 Journal of Guilin University of Technology
基金 国家高技术研究发展计划重大专项(2013AA12A402) 国家自然科学基金项目(61262075/F020702) 广西空间信息与测绘重点实验室开放基金项目(桂科能1103108-25 桂科能1207115-13)
关键词 蚁群算法 多处理机调度 优化 仿真 ant colony algorithm(ACA) multiprocessor scheduling optimization simulation
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