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APPLICATION OF GENETIC ALGORITHMS TO THE SYNTHESIS OF RISER CONFIGURATIONS

机译:遗传算法在RISER配置合成中的应用

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The purpose of this work is to describe the application of Genetic Algorithms in the search of the best configuration of catenary riser systems in deep waters. Particularly, an optimization methodology based on genetic algorithms is implemented on a computer program, in order to seek an optimum geometric configuration for a steel catenary riser in a lazy-wave configuration. This problem is characterized by a very large space of possible solutions; the use of traditional methods is an exhaustive work, since there is a large number of variables and parameters that define this type of system. Genetic algorithms are more robust than the more commonly used optimization techniques. They use random choice as a tool to guide a search toward regions of the search space with likely improvements. Some differences such as the coding of the parameter set, the search from a population of points, the use of objective functions and randomized operators are factors that contribute to the robustness of a genetic algorithm and result in advantages over traditional techniques. The implemented methodology has as baseline one or more criteria established by the experience of the offshore engineer. The implementation of an intelligent methodology oriented specifically to the optimization and synthesis of riser configurations will not only facilitate the work of manipulating a huge mass of data, but also assure the best alternative between all the possible ones, searching in a much larger space of possible solutions than classical methods.
机译:这项工作的目的是描述遗传算法在寻找深水中延伸升性系统的最佳配置中的应用。特别地,基于遗传算法的优化方法在计算机程序上实现,以寻找惰性波形配置中的钢链状立管的最佳几何构造。这个问题的特点是可能的解决方案非常大的空间;传统方法的使用是一种详尽的工作,因为有大量的变量和定义这种类型系统的参数。遗传算法比更常用的优化技术更强大。它们使用随机选择作为工具,以指导朝着搜索空间区域的搜索,这可能有所改进。一些差异,例如参数集的编码,从点群中搜索,客观函数和随机运算符的使用是有助于遗传算法的稳健性的因素,并导致传统技术的优点。实施的方法具有基线,由海上工程师的经验建立了一个或多个标准。专门针对RISER配置的优化和综合的智能方法的实施不仅可以促进操纵大量数据的工作,而且还可以确保所有可能的数据之间的最佳替代方案,在更大的可能空间内搜索解决方案比古典方法。

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