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船舶航行性能优化的模糊遗传算法 被引量:16

Fuzzy-genetic Algorithm of Ship Navigation Performance Optimization
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摘要 模糊遗传算法是一种模糊优化与遗传算法紧密结合的优化方法。它兼有模糊优化的考虑到模糊因素从而更能贴近工程的实际情况和遗传算法的全局寻优能力强的特点。本文中模糊优化采用限界搜索法 ,它可针对模糊非线性规划给出一个特定的清晰解。对应特定水平则委托遗传算法进行寻优。为处理等式和不等式混合约束 ,通过惩罚策略将其吸入遗传算法中染色体的适值。本文采用该方法对船舶航行性能进行优化 ,以船舶的快速性、操纵性和耐波性三个航行性能综合最优为目标函数 ,具体做法是取三个性能指标的线性加权和 ,最后建立的数学模型包括三个等式约束和五个不等式约束。根据以上思想本文用 VC+ + 6.0开发了 Ship PO优化平台 ,并在其上进行船舶航行性能优化计算 ,结果表明 ,该方法耗时少 ,全局寻优能力强 。 Fuzzy genetic algorithm combines fuzzy optimization with genetic algorithm. In this article, the bound search method, which can find a special vivid solution to fuzzy nonlinear programming, is employed to carry out the fuzzy optimization. For the special fuzzy level, the genetic algorithm is used to search the optimum solution. In order to deal with the mixed constraints of equality and inequality, the penalty strategy is used to absorb the constraints into the fitness of the chromosome in genetic algorithm. Ship nevigation performance is optimized by the algorithm. The object function is set up by synthetic optimum of ship's speediness, manoeuvrability and seakeeping performance, and comprises three equlity constraints and five inequality constraints. The ShipPO optimization platform was developed by Vc++6.0.
出处 《中国造船》 EI CSCD 北大核心 2002年第3期7-15,共9页 Shipbuilding of China
关键词 模糊遗传算法 船舶设计 航行性能 优化设计 模糊优化 遗传算法 惩罚策略 快速性 耐波性 操纵性 ship design navigation performance optimization design fuzzy optimization genetic algorithm penalty strategy
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