摘要
装备保障任务调度是否合理、高效是取得现代信息化战争胜负的决定性因素之一,提出了两种改进的粒子群算法对该问题进行优化。针对问题的特点,两种算法均采用基于任务编码的粒子结构,且都采用子群划分的方法以保持种群多样性,①改进算法采用了基于维度分解的分群策略,使算法避免进入高维优化领域,②改进算法采用了杂交操作,有效避免了算法陷入局部最优。仿真结果表明,改进算法相比标准粒子群算法具有更好的性能。
The rationality and efficiency of equipment support mission scheduling is the decisive factor in the outcome of modern information technology war, two improved particle swarm optimization algorithms are presented to solve the problem. Contrapose the characteristic of the problem, task-based encoded particle structure is used in both algorithms, subgroup classification method is used in both algorithms to maintain the population diversity. To avoid entering the high-dimensional optimization, a dimensional decomposition strategy based on decomposition are used in the first improved algorithm, to effectively prevent the algorithm into a local optimum, the genetic algorithm hybrid operation are used in the second improved algorithm. The simulation results show that improved algorithms has better performance.
出处
《计算机工程与设计》
CSCD
北大核心
2012年第8期3105-3109,共5页
Computer Engineering and Design
关键词
粒子群算法
协同算法
杂交操作
装备保障任务调度问题
维度分解
PSO
coordination algorithm
hybrid operation
equipment support mission scheduling problem
dimensional decomposition
