To the weakness of Genetic Algorithm(GA)and based on the character of the practical question, a refined GA is presented in this paper to optimize the unit commitment in the thermal power plant.
本文针对常规遗传算法缺点，根据具体问题的特征，对火电厂内机组优化组合中的遗传算法从各个环节进行了改进，实例计算表明，该方法收敛性好、适应性强、能更有效地达到或接近全局最优。
To the weakness of Genetic Algorithm(GA)and based on the character of the practical question, a refined GA is presented in this paper to optimize the unit commitment in the thermal power plant.
本文针对常规遗传算法缺点，根据具体问题的特征，对火电厂内机组优化组合中的遗传算法从各个环节进行了改进，实例计算表明，该方法收敛性好、适应性强、能更有效地达到或接近全局最优。
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