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Transmission network expansion planning under an improved genetic algorithm

机译:改进遗传算法下的传输网络扩展规划

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This paper describes the application of an improved genetic algorithm (IGA) to deal with the solution of the transmission network expansion planning (TNEP) problem. Genetic algorithms (GAs) have demonstrated the ability to deal with nonconvex, nonlinear, integer-mixed optimization problems, like the TNEP problem, better than a number of mathematical methodologies. Some special features have been added to the basic genetic algorithm (GA) to improve its performance in solving the TNEP problem for three real-life, large-scale transmission systems. Results obtained reveal that GAs represent a promising approach for dealing with such a problem. In this paper, the theoretical issues of GA applied to this problem are emphasized.
机译:本文介绍了改进的遗传算法(IGA)来处理传输网络扩展规划(TNEP)问题的解决方案。遗传算法(气体)已经证明了处理非凸起,非线性,整数混合优化问题的能力,如TNEP问题,优于许多数学方法。基本遗传算法(GA)已添加一些特殊功能,以提高其在解决三个现实生活,大规模传输系统的TNEP问题方面的性能。得到的结果表明,天然气代表了处理此类问题的有希望的方法。在本文中,强调了应用于这个问题的GA的理论问题。

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