Abstract:
To solve subtask allocation problem, a Particle Swarm Optimization(PSO) algorithm is proposed by designing a dual coding method. Pre-constraint is used to produce population. A search strategy based on harmony search is brought into PSO algorithm to avoid its defect of easily plunging into the local optimum. Simulation results of the the classical cases and comparison to other algorithms demonstrate the effectiveness of this algorithm.
Key words:
concurrent design,
subtask allocation,
Particle Swarm Optimization(PSO) algorithm,
dual coding,
harmony search
摘要: 设计一种双重粒子编码方式,提出用于求解子任务分配问题的粒子群优化(PSO)算法。采用预约束方法产生初始种群,根据PSO算法容易陷入局部最优的特点,引入和声搜索策略加以改进。通过对经典实例的仿真分析,并与其他算法进行对比,证明新算法具有较强的寻优能力,收敛速度较快。
关键词:
并行设计,
子任务分配,
粒子群优化算法,
双重编码,
和声搜索
CLC Number:
CHEN Da-Chuan, ZHANG Rong-Guo, HUANG Fu-Liang, LIU Kun. Application of Particle Swarm Optimization Algorithm in Subtask Allocation[J]. Computer Engineering, 2011, 37(24): 183-186.
陈大川, 张荣国, 黄付亮, 刘焜. PSO算法在子任务分配中的应用[J]. 计算机工程, 2011, 37(24): 183-186.