求解舰艇抗损性优化的改进变尺度混沌遗传算法

Improved Mutative Scale Chaos Gene Algorithm of Ship Anti-vulnerability Optimization

为满足舰艇抗损性优化的需要,构建了优化的数学模型;针对以往该类问题求解算法时间长、易早熟的不足,对传统的遗传算法进行了改进。首先通过适应度函数的标定,自适应的调节了个体选择的概率;然后对交叉概率和变异概率进行了动态修正;不仅如此,利用变尺度混沌优化算法对种群中的较优个体进行了混沌搜索,避免了陷入局部最优解。案例优化结果的对比表明,改进的遗传算法能够快速地搜索到全局最优解,特别是避免了不成熟的收敛,较好地指导了抗损性的优化设计。

To make anti-vunlerability ability optimization,the math model of optimization and its improved gene arithmetic which can avoid long calculation time and premature convergence are founded.The individual selection probability is adjusted adaptively through fitness function modification firstly.And then,the cross and mutation probability is modified dynamically.Not only the improve measures mentioned above,the better solutions of population is optimized through chaos search which can avoid local best solution.The case optimization results indicate that the improved gene arithmetic can search the optimal solution quickly and can avoid premature convergence.The improved algorithm can guide anti-vunlerability optimization precisely.