Semnan University Press Journal of Modeling in Engineering 2008-4854 21 75 2023 12 22 Optimizing the coefficients of the particle swarm optimization algorithm to solve the problem of economic dispatching to reduce the emission of environmental pollutants Optimizing the coefficients of the particle swarm optimization algorithm to solve the problem of economic dispatching to reduce the emission of environmental pollutants 297 307 8348 10.22075/jme.2023.28549.2341 FA Amirhossein Oudi Department of Chemical Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran Shiva Yarmohammadian Department of Chemical Engineering, Faculty of Engineering, Razi University, Kermanshah, Iran Maryam Hosseini Department of Chemical Engineering, Faculty of Engineering, Kashan, Iran. Ebrahim Nemati Lay Department of Chemical Engineering, Faculty of Engineering, University of Kashan,, Kashan, Iran Journal Article 2022 09 28 Environmental issues due to the emission of pollutants produced by fossil fuel power plants have recently become an important issue. In this study, the coefficients of particle swarm optimization (PSO) algorithm to solve the problem of economic dispatching to reduce the emission of environmental pollutants were obtained. According to Clerk method, personal learning coefficient was equal to 1.4962, global learning coefficient was equal to 1.4962 and inertia coefficient was equal to 0.73. Also, the penalty coefficient according to the Co evolution particle swarm (CPSO) optimization algorithm was 15.8. As a result, optimization of coefficients by Taguchi method, it showed that the optimal value of personal learning coefficient is equal to 1.5, global learning coefficient is equal to 1.5, inertia coefficient is equal to 0.70 and penalty coefficient is equal to 15, in this case the amount emission of environmental pollutants were reduced by 6.5% compared to the coefficients determined by Clerk and 1.2% compared to the coefficients determined by the Co evolution particle swarm (CPSO) optimization algorithm. Environmental issues due to the emission of pollutants produced by fossil fuel power plants have recently become an important issue. In this study, the coefficients of particle swarm optimization (PSO) algorithm to solve the problem of economic dispatching to reduce the emission of environmental pollutants were obtained. According to Clerk method, personal learning coefficient was equal to 1.4962, global learning coefficient was equal to 1.4962 and inertia coefficient was equal to 0.73. Also, the penalty coefficient according to the Co evolution particle swarm (CPSO) optimization algorithm was 15.8. As a result, optimization of coefficients by Taguchi method, it showed that the optimal value of personal learning coefficient is equal to 1.5, global learning coefficient is equal to 1.5, inertia coefficient is equal to 0.70 and penalty coefficient is equal to 15, in this case the amount emission of environmental pollutants were reduced by 6.5% compared to the coefficients determined by Clerk and 1.2% compared to the coefficients determined by the Co evolution particle swarm (CPSO) optimization algorithm. https://modelling.semnan.ac.ir/article_8348_7e16047f60d03451d22275bd89d7416d.pdf