摘要
尝试用粒子群优化理论(PSO)求解防空群火力分配决策的优化模型。首先把约束方程作为罚函数加入到原目标中,变为无约束的优化问题。假设通过粒子群算法得到一组局部最优点X1,将X1转化为二进制编码。然后采用遗传算法中的一个概率随机改变二进制表达式中的某些位,使得编码发生变化,形成一组新的解X2。比较X1和X2的适应值,舍去比X1劣的解,保存比X1优的解,最后采用粒子群算法在X2的领域内进行寻优。
The Particle Swarm Optimization （PSO） is used to solve the optimization model of air defense forces group fire distribution decision. First regard the restraining equation as fine function and join it in the original goal, turn it to a unconstrained optimization question. Supposing one group of the partial optimum dots： X1, is gotten through PSO, turn X1 to the binary code, Then, adopt a probability random in the hereditary algorithm to change some places in the binary formula, move the code, and form a new group of solutions： X2. Compare the adaptation value of X1 and X2, abandon solutions worse than X1 and keep solutions more excellent than X1. Finally, use PSO to seek optimum solutions in X2.
出处
《兵工自动化》
2008年第4期10-11,14,共3页
Ordnance Industry Automation
关键词
粒子群
火力分配
优化
Particle swarm
Firepower assignment
Optimization
