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A Modified Teaching-Learning Optimization Algorithm for Economic Load Dispatch Problem

机译:一种改进的经济负荷调度问题教学学习优化算法

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For the original Teaching-learning algorithm, it is weak in global search and prone to local search when solving complex optimization problems of high dimension. A modified algorithm based on space reverse-solution is proposed in this paper. Improvement of teacher phrase is based on the chaotic mapping and that of student phrase is based on the multi learning strategy. Then Self-learning phrase is added. The modified algorithm is applied to the complex high-dimensional benchmark functions for simulation experiments. Finally, the modified algorithm is applied to two typical power load distribution problems including 13 units and 40 units. The validity of the algorithm is verified from the aspects of convergence speed, convergence accuracy and stability.
机译:对于原始教学学习算法,在解决高尺寸的复杂优化问题时,它在全球搜索和易于局部搜索中的弱点。本文提出了一种基于空间反向解决方案的修改算法。教师短语的改进是基于混沌映射,学生短语的基于多学习策略。然后添加自学习短语。修改的算法应用于模拟实验的复杂高维基准函数。最后,修改的算法应用于两个典型的功率负载分布问题,包括13个单位和40个单元。算法的有效性是从收敛速度,收敛精度和稳定性的方面验证的。

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