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首页> 外文期刊>IEEE Transactions on Power Systems >An extensible genetic algorithm framework for problem solving in a common environment
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An extensible genetic algorithm framework for problem solving in a common environment

机译:通用环境中解决问题的可扩展遗传算法框架

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摘要

The authors describe an object-oriented framework for solving mathematical power system programs using genetic algorithms (GAs). The advantages of this framework are its extensibility, modular design and accessibility to existing programming code. The framework also incorporates a graphical user interface that may be used to build new GAs as well as run GA simulations. Two power system problems are solved by implementing genetic algorithms using the said framework. The first is a continuous optimization problem and the second an integer programming problem. The authors illustrate the flexibility of the framework as well as its other features on their test problems.
机译:作者介绍了一种使用遗传算法(GA)求解数学动力系统程序的面向对象的框架。该框架的优势在于其可扩展性,模块化设计以及对现有编程代码的可访问性。该框架还包含图形用户界面,可用于构建新的GA以及运行GA模拟。通过使用所述框架实施遗传算法,解决了两个电力系统问题。第一个是连续优化问题,第二个是整数规划问题。作者说明了该框架的灵活性以及其测试问题的其他功能。

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