A novel multiobjective evolutionary algorithm for environmental/economic power dispatch

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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.”
Multiobjective Particle Swarm Algorithm With Fuzzy Clustering for Electrical Power Dispatch (2008, methodology): “Nondominated sorting genetic algorithm (NSGA) [13], niched Pareto genetic algorithm (NPGA) [14], strength Pareto evolutionary algorithm (SPEA) [2], multiobjective stochastic search technique (MOSST) [15], Tabu Search [16], NSGA II [17], [18], multiobjective particle swarm optimization (MOPSO) [20], ”
Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect (2006, background): “HE objective of the economic dispatch problem (EDP) of electric power generation, whose characteristics are complex and highly nonlinear, is to schedule the committed generating unit outputs so as to meet the required load demand at minimum operating cost while satisfying all unit and system equalit”
Economic-emission dispatch problem: A semi-definite programming approach (2014, methodology): “More recent approaches use evolutionary algorithms [14, 15] including particle swarm optimization (PSO) method [16, 17], genetic algorithms (GA) [9], bacterial foraging (BF) method [18, 19] and differential evolution [20].”