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In this paper, we develop an optimal control approach of pollution and emission reduction subject to convection-diffusion transport equations. A linked simulation-optimization method has been proposed, based on solving the convection-diffusion transport equations and solving the optimization procedure. The governing equations of the convection-diffusion-reaction equations with pollution sources are discretized by the splitting improved upwind finite volume scheme while the constrained differential evolution (DE) algorithm is applied to solve the global optimization procedure. The advantage of the approach is the external linking of the numerical simulation and the optimization procedure, minimizing both the weighted deviation between simulated concentrations and the smallest allowable concentrations at observation sites and the emission reduction cost at the pollution sources at same time. Numerical tests first check the convergence of numerical methods. Numerical experiments then show the performance of the approach for solving the optimal control problems of pollution and cost of emission reduction. The developed optimal control approach is efficient and it can be applied to more complex problems in applications.
}, issn = {2617-8710}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/ijnam/10016.html} }In this paper, we develop an optimal control approach of pollution and emission reduction subject to convection-diffusion transport equations. A linked simulation-optimization method has been proposed, based on solving the convection-diffusion transport equations and solving the optimization procedure. The governing equations of the convection-diffusion-reaction equations with pollution sources are discretized by the splitting improved upwind finite volume scheme while the constrained differential evolution (DE) algorithm is applied to solve the global optimization procedure. The advantage of the approach is the external linking of the numerical simulation and the optimization procedure, minimizing both the weighted deviation between simulated concentrations and the smallest allowable concentrations at observation sites and the emission reduction cost at the pollution sources at same time. Numerical tests first check the convergence of numerical methods. Numerical experiments then show the performance of the approach for solving the optimal control problems of pollution and cost of emission reduction. The developed optimal control approach is efficient and it can be applied to more complex problems in applications.