单位承诺的基因互补遗传算法

ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501) Pub Date : 2001-08-18 DOI:10.1109/ICEMS.2001.970758

Liu Maojun, Tong Tiaosheng

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引用次数: 8

摘要

提出了一种改进的遗传算法求解机组承诺问题，并构造了三种遗传算子。为了提高算法的收敛速度，防止算法收敛于局部最优解，提出了一种基因互补技术，并将其应用于改进的遗传算法中，称为基因互补遗传算法(GCGA)。仿真结果表明，GCGA是一种求解UCP问题的有效算法。

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A gene complementary genetic algorithm for unit commitment

This paper presents a modified genetic algorithm solution to the unit commitment problem (UCP), and constructs three kinds of genetic operators. To enhance convergence rate of the algorithm and prevent converging at a local optimal solution, a gene complementary technology is proposed and is applied to the modified genetic algorithm, which is called a gene complementary genetic algorithm (GCGA). Simulation results show that GCGA is a very efficient algorithm for solution to UCP.

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ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)

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