基于遗传算法的吊放声纳搜潜策略优化

摘要

Aim at the problem of dipping sonar antisubmarine search path,a search tactics based on GA is given. In the algorithm,the initial population is optimized by Real-number coding,the evolution algorithm is optimized by turntable bet and expected value method. Simulation Results show that the application of the Genetic Algorithm for dipping sonar submarine search path optimization is a high value method,but it is a complex and large calculation algorithm,therefore further research and simplification are required in project implementation.%针对吊放声纳搜潜策略问题，在平均分配每点的搜索时间的典型搜潜策略的基础上，采用遗传算法优化搜潜策略中的吊点选择，进而给出合理的吊放声纳搜潜路径。算法中，利用实数编码优化初始种群，采用轮盘赌和期望值相结合的混合选择策略优化种群的进化。仿真运算表明：采用遗传算法优化吊放声纳搜潜路径是一种具有研究价值的方法，但算法复杂，计算量大，工程实现还需要进一步研究简化。