@article{Fahad Parvez Mahdi_Pandian Vasant_M. Abdullah-Al-Wadud_Junzo Watada_Vish Kallimani_Patrick Yeoh Siew Fai_2016, title={QUANTUM PARTICLE SWARM OPTIMIZATION FOR ECONOMIC DISPATCH PROBLEM USING CUBIC FUNCTION CONSIDERING POWER LOSS CONSTRAINT}, volume={13}, url={https://geomatejournal.com/geomate/article/view/1505}, abstractNote={<p>In this paper, quantum computing (QC) inspired particle swarm optimization (QPSO) technique is <br>utilized to solve economic dispatch (ED) problem, which has strong, robust and reliable search capability with <br>powerful convergence properties. Here, authors use cubic criterion function to represent ED instead of the <br>traditional quadratic function, to make the system robust against nonlinearities of actual power generators. Power <br>balance, power loss and generator limit constraints are considered in this research work. To show the efficiency <br>and robustness of the proposed method, authors have compared the obtained results with other algorithms like <br>PSO and GA for ED problem on 3-unit and 5-unit power generating systems. The obtained results demonstrate <br>QPSO’s superiority over other methods in terms of providing quality solutions with significant amount of <br>robustness and computationally efficiency.</p>}, number={37}, journal={GEOMATE Journal}, author={Fahad Parvez Mahdi and Pandian Vasant and M. Abdullah-Al-Wadud and Junzo Watada and Vish Kallimani and Patrick Yeoh Siew Fai}, year={2016}, month={Nov.}, pages={44–50} }