In offshore oil and gas production, the increasingly complex line system and relatively fixed incidence direction of external loadings have led to asymmetrically distributed mooring lines in floating production systems (FPSs). This study presents an approach for the optimal design of asymmetrically arranged mooring systems in FPSs, considering the mooring radius, azimuth, separate angle, number of lines and three segment lengths as design variables. A series of sample mooring configurations were generated via the constrained Latin hypercube sampling method and executed by a time-domain numerical model. An improved particle swarm optimization (PSO) method involving both continuous and discrete design variables in a constrained design space was applied to mooring optimization. The radial basis function (RBF) model was trained by the sample data and applied as a surrogate model to replace the expensive finite element simulations. A case study of a deep-water semisubmersible platform was presented to demonstrate the implementation of the optimization procedure. The results showed that the improved PSO exhibited fast convergence and strong robustness. The offset of the floating platform was reduced by 8.29 % via the asymmetrical mooring pattern.

在海上油气生产中，日益复杂的管线系统和相对固定的外部载荷入射方向导致浮式生产系统（FPS）中系泊管线的分布不对称。本研究提出了一种FPSs中不对称布置的系泊系统的优化设计方法，考虑系泊半径、方位角、分离角、线数和三段长度作为设计变量。通过约束拉丁超立方采样方法生成了一系列样本系泊配置，并通过时域数值模型执行。将一种改进的粒子群优化（PSO）方法应用于系泊优化，该方法涉及受限设计空间中的连续和离散设计变量。径向基函数（RBF）模型通过样本数据进行训练，并作为替代模型来取代昂贵的有限元模拟。提出了一个深水半潜式平台的案例研究来演示优化程序的实施。结果表明，改进后的PSO收敛速度快、鲁棒性强。通过非对称系泊方式，浮动平台的偏移量减少了8.29%。