DocumentCode :
594224
Title :
A new multi-objective particle swarm optimization for economic environmental dispatch
Author :
Bilil, H. ; Ellaia, Rachid ; Maaroufi, Mohamed
Author_Institution :
Mohammadia Sch. of Eng., Mohammed V Univ. - Agdal, Rabat, Morocco
fYear :
2012
fDate :
5-6 Nov. 2012
Firstpage :
1
Lastpage :
6
Abstract :
This paper investigates a new approach of computation using particle swarm in order to resolve economic environmental dispatch problem. This approach is called accelerated multiobjective particle swarm optimization (AMOPSO) which incorporates vector function as objective function and uses matrix computation and updates solutions set, in each iteration, for developing the Pareto front unlike the existing multi-objective algorithms which use an external archive. We apply this approach to resolve the problem which treats fuel cost, NOx emissions and active power losses as competing objectives.
Keywords :
matrix algebra; particle swarm optimisation; AMOPSO; Pareto front; accelerated multiobjective particle swarm optimization; economic environmental dispatch problem; matrix computation; multiobjective algorithms; new multiobjective particle swarm optimization; objective function; vector function; Acceleration; Economics; Fuels; Optimization; Particle swarm optimization; Sociology; Statistics; Optimal economic environmental dispatch; matrix computation; multi-objective optimization; particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Complex Systems (ICCS), 2012 International Conference on
Conference_Location :
Agadir
Print_ISBN :
978-1-4673-4764-8
Type :
conf
DOI :
10.1109/ICoCS.2012.6458597
Filename :
6458597
Link To Document :
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