Cite Article

NMEP based Gaussian Mutation Process on Optimizing Fitness Function for MOEED

Choose citation format

BibTeX

@article{IJASEIT2285,
   author = {M. R. M. Ridzuan and E. E. Hassan and A. R. Abdullah and N. Bahaman and A. F. A. Kadir},
   title = {NMEP based Gaussian Mutation Process on Optimizing Fitness Function for MOEED},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {5},
   year = {2017},
   pages = {1840--1846},
   keywords = {economic dispatch; artificial intelligence; multi objective function.},
   abstract = {

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.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=2285},    doi = {10.18517/ijaseit.7.5.2285} }

EndNote

%A M. Ridzuan, M. R.
%A Hassan, E. E.
%A Abdullah, A. R.
%A Bahaman, N.
%A A. Kadir, A. F.
%D 2017
%T NMEP based Gaussian Mutation Process on Optimizing Fitness Function for MOEED
%B 2017
%9 economic dispatch; artificial intelligence; multi objective function.
%! NMEP based Gaussian Mutation Process on Optimizing Fitness Function for MOEED
%K economic dispatch; artificial intelligence; multi objective function.
%X 

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.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=2285 %R doi:10.18517/ijaseit.7.5.2285 %J International Journal on Advanced Science, Engineering and Information Technology %V 7 %N 5 %@ 2088-5334

IEEE

M. R. M. Ridzuan,E. E. Hassan,A. R. Abdullah,N. Bahaman and A. F. A. Kadir,"NMEP based Gaussian Mutation Process on Optimizing Fitness Function for MOEED," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 5, pp. 1840-1846, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.5.2285.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - M. Ridzuan, M. R.
AU  - Hassan, E. E.
AU  - Abdullah, A. R.
AU  - Bahaman, N.
AU  - A. Kadir, A. F.
PY  - 2017
TI  - NMEP based Gaussian Mutation Process on Optimizing Fitness Function for MOEED
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 5
Y2  - 2017
SP  - 1840
EP  - 1846
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - economic dispatch; artificial intelligence; multi objective function.
N2  - 

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.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=2285 DO - 10.18517/ijaseit.7.5.2285

RefWorks

RT Journal Article
ID 2285
A1 M. Ridzuan, M. R.
A1 Hassan, E. E.
A1 Abdullah, A. R.
A1 Bahaman, N.
A1 A. Kadir, A. F.
T1 NMEP based Gaussian Mutation Process on Optimizing Fitness Function for MOEED
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 5
YR 2017
SP 1840
OP 1846
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 economic dispatch; artificial intelligence; multi objective function.
AB 

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.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=2285 DO - 10.18517/ijaseit.7.5.2285