Environmental/economic power dispatch using a fuzzified multi-objective particle swarm optimization algorithm

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A multi-objective chaotic ant swarm optimization for environmental/economic dispatch (2010, methodology): “WangandSinghusedan improvedparticle swarmoptimization (PSO) algorithm to achieve the reasonable tradeoff between multiple objectives including the total generation cost, emission, and transmission power loss and got some better results [14–16].”
A self-learning TLBO based dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads (2014, methodology): “Similarly, the 5-unit system is employed and the data is taken from [33].”
A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatch (2012, methodology): “A straightforward constraint checking approach, called the rejecting strategy, was proposed in [10,39,40] to deal with the constraints of the EED problem.”
Particle swarm optimization algorithm embedded with maximum deviation theory for solving multi-objective flexible job shop scheduling problem (2015, methodology): “* S. S. Mahapatra mahapatrass2003@yahoo.com Manas Ranjan Singh manasranjan.singh@gmail.com Madhusmita Singh madhus_mita@yahoo.com Nibedita Jagadev queennibedita@gmail.com 1 Department of Mechanical Engineering, National Institute of Technology Rourkela, Rourkela, India 2 Department of Computer Scien”