DOI : https://doi.org/10.18517/ijaseit.7.5.2285

NMEP based Gaussian Mutation Process on Optimizing Fitness Function for MOEED

M. R. M. Ridzuan (1), E. E. Hassan (2), A. R. Abdullah (3), N. Bahaman (4), A. F. A. Kadir (5)
(1) Center for Robotics and Industrial Automation (CeRIA), Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Malaysia
(2) Center for Robotics and Industrial Automation (CeRIA), Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Malaysia
(3) Center for Robotics and Industrial Automation (CeRIA), Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Malaysia
(4) Department of Computer System and Communication, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Malaysia
(5) Center for Robotics and Industrial Automation (CeRIA), Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Malaysia
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How to cite (IJASEIT) :
M. Ridzuan, M. R., et al. “NMEP Based Gaussian Mutation Process on Optimizing Fitness Function for MOEED”. International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 5, Oct. 2017, pp. 1840-6, doi:10.18517/ijaseit.7.5.2285.
Citation Format :
The increment of Economic Dispatch (ED) problem is very distressing today. In view of countless of the researchers doing the research to minimize the ED problem day after day, the multi objective New Meta Heuristic Evolutionary Programming (NMEP) techniques are proposed to optimize the multi objective function in ED problem called as Multi Objective Environmental Economic Dispatch (MOEED). The techniques mimic the original Meta Heuristic Evolutionary Programming (Meta-EP) and merge with Artificial Immune System (AIS) with some improvement in Gaussian mutation process and cloning process. The NMEP produced two objective function result simultaneously by exercising the weighted sum method. In order to justify the result, the comparison between the NMEP and Meta-EP techniques is conducted with difference case number of alpha. Therefore, the outcome of the simulation shows the NMEP approach is better than Meta-EP in the both case numbers of alpha. The simulation is operated using MATLAB simulation based on standard IEEE 26 bus system in the laboratory.

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