文章基本信息

标题：HYBRID DIFFERENTIAL EVOLUTION-ANT COLONY OPTIMIZATION FOR ECONOMIC LOAD DISPATCH PROBLEM
本地全文：下载
作者：N.A. RAHMAT ; I. MUSIRIN
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：48
期号：2
页码：680-690
出版社：Journal of Theoretical and Applied
摘要：A distinctive optimization technique known as Ant Colony Optimization (ACO) has gained huge popularity in these recent years due to its flexibility and the ability to avoid reaching local optima. This optimization approach has become a candidate approach for many optimization problems. Unfortunately, this attractive algorithm suffers several downsides including stagnation and slow convergence toward optimal solution. Thus, a new algorithm, termed as Differential Evolution Ant Colony Optimization (DEACO) has been modelled to compensate the drawbacks. The algorithm was utilized to solve economic load dispatch problem in order to verify its performance. Economic Load Dispatch (ELD) problem concerns the planning of generators outputs that can meet load demand at minimum operating cost. Moreover, in this research, several ant parameters, including number of ants and nodes were manipulated to investigate the behaviour of DEACO algorithm. Comparative studies between DEACO and conventional ACO suggested that the new algorithm has successfully overcome the weaknesses of classical ACO.
关键词：Ant Colony Optimization (ACO); Differential Evolution (DE); Economic Load Dispatch (ELD)