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Standing wave optimization of SMB using a hybrid simulated annealing and genetic algorithm (SAGA)

Authors
  • Cauley, Fattaneh G.1
  • Cauley, Stephen F.2
  • Wang, Nien-Hwa Linda3
  • 1 Pepperdine University, Seaver College, Malibu, CA, 90263, USA , Malibu (United States)
  • 2 Purdue University, School of Electrical Engineering, West Lafayette, IN, 47907, USA , West Lafayette (United States)
  • 3 Purdue University, School of Chemical Engineering, West Lafayette, IN, 47907, USA , West Lafayette (United States)
Type
Published Article
Journal
Adsorption
Publisher
Springer US
Publication Date
Apr 08, 2008
Volume
14
Issue
4-5
Pages
665–678
Identifiers
DOI: 10.1007/s10450-008-9119-8
Source
Springer Nature
Keywords
License
Yellow

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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