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An enhanced non-dominated sorting based fruit fly optimization algorithm for solving environmental economic dispatch problem

机译:一种改进的基于非支配排序的果蝇优化算法,用于解决环境经济调度问题

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A fruit fly optimization algorithm based on the enhanced non-dominated sorting (ESFOA) is proposed to solve the environmental economic dispatch (EED) problem. To measure the difference between two non-dominated solutions, the concept of the enhanced non-dominance is defined, and the degrees of dominance and non-dominance are presented. To enhance the parallel search ability, multiple fruit flies groups are used to perform evolutionary search in the ESFOA. In the vision-based search process, the best fruit fly is determined according to the enhanced non-dominance value. To guarantee the feasibility of the new solutions, an effective heuristic mechanism to handle constraints is adopted to repair the infeasible solutions. Meanwhile, an external archive is used to store the non-dominated solutions. The influence of parameter setting is investigated based on the Taguchi method of design of experiment, and a suitable parameter setting is suggested. Finally, numerical tests are carried out by using the IEEE 30-bus benchmark. The comparisons to some existing methods by using the technique for order preference by similarity to ideal solution (TOPSIS) demonstrate the effectiveness of the proposed algorithm.
机译:提出了一种基于增强非支配排序(ESFOA)的果蝇优化算法,以解决环境经济调度(EED)问题。为了测量两个非支配解之间的差异,定义了增强型非支配性的概念,并介绍了支配性和非支配性的程度。为了增强并行搜索能力,在ESFOA中使用多个果蝇组来进行进化搜索。在基于视觉的搜索过程中,最佳果蝇是根据增强的非优势值确定的。为了保证新解决方案的可行性,采用了一种有效的启发式机制来处理约束,以修复不可行的解决方案。同时,外部档案库用于存储非主导解决方案。基于实验设计的田口方法,研究了参数设置的影响,并提出了合适的参数设置方法。最后,使用IEEE 30总线基准测试进行了数值测试。通过使用与理想解决方案(TOPSIS)相似的顺序偏好技术,与一些现有方法进行比较,证明了所提算法的有效性。

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