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Research on facility layout optimization algorithm of deep-water semi-submersible drilling platform

机译:深水半潜水钻井平台设施布局优化算法研究

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摘要

We aimed to create a facility layout design of semi-submersible drilling platform (DSDP) with performance constraints. The Boltzmann survival mechanism of simulated annealing algorithm was introduced into the replacement strategy of genetic algorithm to form an improved genetic algorithm called genetic and simulated annealing algorithm (GASA). The new algorithm alleviates the combination explosion and premature convergence of the traditional genetic algorithm. The layout problem of DSDP is efficiently solved by using this new algorithm. When the number of layout objects increases, GASA's performance is better than that of the genetic algorithm.
机译:我们旨在创建具有性能约束的半潜式钻井平台(DSDP)的设施布局设计。 仿真退火算法的Boltzmann存活机制被引入遗传算法的替代策略,形成称为遗传和模拟退火算法(GASA)的改进遗传算法。 新算法减轻了传统遗传算法的组合爆炸和早产。 通过使用这种新算法,DSDP的布局问题是有效解决的。 当布局对象的数量增加时,GASA的性能优于遗传算法。

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