%0 Journal Article
%T Differential Evolution Immunized Ant Colony Optimization Technique in Solving Economic Load Dispatch Problem
%A N. A. Rahmat
%A I. Musirin
%J Engineering
%P 157-162
%@ 1947-394X
%D 2013
%I Scientific Research Publishing
%R 10.4236/eng.2013.51B029
%X <span><span><span><span><span style=\"color:black;\">Since the introduction of Ant Colony Optimization (ACO) technique in 1992, the algorithm starts to gain popularity due to its attractive features. However, several shortcomings such as slow convergence and stagnation motivate many researchers to stop further implementation of ACO. Therefore, in order to overcome these drawbacks, ACO is proposed to be combined with Differential Evolution (DE) and cloning process. This paper presents Differential Evolution Immunized Ant Colony Optimization (DEIANT) technique in solving economic load dispatch problem. The combination creates a new algorithm that will be termed as Differential Evolution Immunized Ant Colony Optimization (DEIANT). DEIANT was utilized to optimize economic load dispatch problem. A comparison was made between DEIANT and classical ACO to evaluate the performance of the new algorithm.</span></span></span></span></span></a><span><span><span><span><span style=\"color:black;\"> </span></span></span></span></span><span><span><span style=\"color:black;\">In realizing the effectiveness of the proposed technique, IEEE 57-Bus Reliable Test System (RTS) has been used as the test specimen. Results obtained from the study revealed that the proposed DEIANT has superior computation time.</span><span style=\"color:black;\"></span></span></span>
%K Ant Colony Optimization (ACO)
%K Differential Evolution (DE)
%K Differential Evolution Immunized Ant Colony Opti-mization (DEIANT)
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=26654