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Standing wave optimization of SMB using a hybrid simulated annealing and genetic algorithm (SAGA) |
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| Authors: | Fattaneh G. Cauley Stephen F. Cauley Nien-Hwa Linda Wang |
| Affiliation: | 1. Seaver College, Pepperdine University, Malibu, CA, 90263, USA 2. School of Electrical Engineering, Purdue University, West Lafayette, IN, 47907, USA 3. School of Chemical Engineering, Purdue University, West Lafayette, IN, 47907, USA |
| Abstract: | In this paper we draw on two stochastic optimization techniques, Simulated Annealing and Genetic Algorithm (SAGA), to create a hybrid to determine the optimal design of nonlinear Simulated Moving Bed (SMB) systems. A mathematical programming model based on the Standing Wave Design (SWD) offers a significant advantage in optimizing SMB systems. SAGA builds upon the strength of SA and GA to optimize the 16 variables of the mixed-integer nonlinear programming model for single- and multi-objective optimizations. The SAGA procedure is shown to be robust with computational time in minutes for single-objective optimization and in a few hours for a multi-objective optimization, which is comprised of more than one hundred points. |
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