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- W2977886821 abstract "Product oil blending has a significant impact on refinery profits.Product oil blending optimization is a nonlinear constrained optimization problem,which is challenging for traditional evolutionary algorithms,because they lack structural information and have a larger search space.This paper presents a method for product oil blending optimization based on a piecewise linear surrogate model,which includes piecewise linear modeling and piecewise linear optimization.The nonlinear properties of the product oil blend are approximated by a surrogate model based on a piecewise linear function to transform the original problem into a piecewise linear programming problem.Then,a differential evolution algorithm is used to search linear sub-regions for the globally optimal solution to improve the solution speed of the evolutionary algorithm and guide its search away from local optimums.This method is used to solve a recipe optimization problem for gasoline blending,with the feasibility and effectiveness confirmed by the optimization results." @default.
- W2977886821 created "2019-10-10" @default.
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- W2977886821 date "2012-01-01" @default.
- W2977886821 modified "2023-09-25" @default.
- W2977886821 title "Product oil blending optimization based on a piecewise linear surrogate model" @default.
- W2977886821 hasPublicationYear "2012" @default.
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