基于遗传算法的VLCC货油舱分舱优化

Subdivision optimization of VLCC Cargo tanks based on genetic algorithm

探讨以减小静水弯矩为目标的超大型油船分舱优化方法。建立以横舱壁位置为参变量的参数化分舱模型,编程实现典型工况配载计算;建立基于遗传算法的优化模型,实现在主尺度、船型和货油舱区域总长确定的情况下,以最小静水弯矩为优化目标的货油舱横舱壁位置优化。实际应用结果表明,该方法能快速高效地找到满足强制规范要求的静水弯矩最优的分舱方案。

Studies the methods for subdivision optimization of VLCC with the objective of minimizing still water bending moment.The longitudinal position of the main transverse bulkhead are parametrically modeled and regarded as design variables.The application program for calculating the typical loading condition is developed.The optimization model based on genetic algorithm method is built up.It can be used for optimizing the transverse bulkhead position of cargo tanks with the objective of minimizing still water bending moment when the main dimensions,ship form and cargo area length are determined.The example shows that this method can be applied to find a subdivision rapidly and efficiently,which satisfies the mandatory rules requirements and with minimum still water bending moment.