Quantum particle swarm optimization for multiobjective combined economic emission dispatch problem using cubic criterion function

Mahdi, F.P. and Vasant, P. and Rahman, M.M. and Abdullah-Al-Wadud, M. and Watada, J. and Kallimani, V. (2017) Quantum particle swarm optimization for multiobjective combined economic emission dispatch problem using cubic criterion function. 2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017.

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Abstract

In this research, quantum particle swarm optimization (QPSO) is utilized to solve multiobjective combined economic emission dispatch (CEED) problem formulated using cubic criterion function considering a uni wise max/max price penalty factor. QPSO is implemented on a 6-unit power generation system and compared with Lagrangian relaxation, particle swarm optimization (PSO) and simulated annealing (SA). The obtained results verified the effectiveness and demonstrate the robustness of QPSO method. This research suggests that QPSO can be used as an effective and robust tool in other power dispatch problems. © 2017 IEEE.

Item Type: Article
Impact Factor: cited By 0
Departments / MOR / COE: Departments > Fundamental & Applied Sciences
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 22 Apr 2018 14:41
Last Modified: 22 Apr 2018 14:41
URI: http://scholars.utp.edu.my/id/eprint/20112

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