A new multiobjective evolutionary algorithm for environmental/economic power dispatch

By A.A. Abido. 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262), 2001

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Solving Multi-Objective Economic Dispatch Problem Via Semidefinite Programming (2013, methodology): “The cost coefficients, power generation limits, and details of the bus and line data can be found in [12], [36] and, [37], respectively.”
Economic-emission dispatch problem: A semi-definite programming approach (2014, background): “Details of the bus and line data can be found in [55].”
A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatch (2012, methodology): “In order to compare with the results in [2–5], the compromise solution is also identified at the end of our algorithm.”
A niched Pareto genetic algorithm for multiobjective environmental/economic dispatch (2003, methodology): “[22], only two individuals are randomly selected for tournament.”
Environmental/economic power dispatch using multiobjective evolutionary algorithms (2003, methodology): “It is worth mentioning that, unlike the technique presented in [15], the fitness of a population member is determined only from the individuals stored in the external set.”
Ship Pipe Routing Design Using NSGA-II and Coevolutionary Algorithm (2016, background): “For Pareto optimal chromosome sets with Nobj objectives and M individuals, a membership function μi denotes the ith objective function of an individual in Pareto optimal solutions, which is defined in [39]:”