基于粒子群算法的浮筒配置优化问题的研究

针对传统的验证法在解决浮筒配置问题中存在的计算量大、计算时间长、工作重复性强等缺点，提出了一种将浮筒纵向位置配置和浮筒充气量综合考虑、一体优化的方法。文章将各种合理性校验准则作为约束条件，通过逼近沉艇起浮瞬间和浮起后的平衡状态，来求取各对浮筒的纵向位置和充气量，将浮筒配置问题转换为一个多目标、多约束的最优化问题。在此基础上，根据粒子群优化算法的特点，提出了一种双向搜索策略，来求解浮筒配置优化问题。这种方法简单实用，计算时间短，无需人工干预，算法运行一次可获得多组配置方案供决策人员选择。算例表明用这种方法来解决浮筒配置问题是可行的、有效的。

Study on Optimization of Buoy-arranging Based On Particle Swarm Optimization

Considering the shortcoming of traditional method in solving buoy-arranging problem, a new approach is presented. An optimized model of buoy-arranging is introduced, and an improved particle swarm optimization method, adopting two-orientation searching strategy, is proposed to obtain the appropriate longitudinal location and the gas volume of each pair of the buoys. This approach is easy to carry out and has high efficiency. Moreover, this approach can provide multiple solutions for the decision-maker in a single running. The example shows the approach is feasible and effective.