So far numerous scientific, works have been developed by.Researchers dealt with the optimal operation scheduling under.Different loading conditions and objectives. At first conventional,,Economic scheduling has been proposed as a solution for the.Optimization problem through finding an optimal set of generators.To satisfy load demand and operational constraints in an economical manner [6e8]. Due to the environmental concerns and.Pollutants emission from traditional fossil fuel units singleobjective optimization, could no longer be satisfactory in. The.Mentioned problem. To involve emission as a separate goal multiobjective optimization, techniques have been developed in. Articles.In order to choose a definite number of units for supplying the load.Under a certain condition taking into account minimum levels of.Cost and emission for grid operation []. Recently evolutionary 9e13,,Algorithms such as GA (Genetic Algorithm), PSO (Particle Swarm.Optimization) and so on have been increasingly proposed for.Solving the optimization problem because of their inherent.Nonlinear mapping simplicity and, powerful search capabilities.[]. Hybrid 13e18 approaches such as Fuzzy-based evolutionary.
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