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Application of multi-objective optimization in the design of SMB in chemical process industry

DOI: 10.1016/s1570-7946(03)80458-3
  • Multi-Objective Optimization
  • Smb
  • Varicol
  • Genetic Algorithm
  • Pareto
  • Computer Science
  • Design
  • Mathematics


Abstract A new optimization and design strategy, multi-objective optimization, is applied to improve the performance of Simulated Moving Bed (SMB) and its modification, the Varicol systems with or without reactions. The capabilities of the new approach are illustrated considering three different applications of SMB (and Varicol process), namely, chiral drug separation, production of high concentrated fructose syrup and synthesis of methyl acetate ester. The non-dominated sorting genetic algorithm (NSGA) is used in obtaining Pareto optimal solutions. It was found that significant improvement is possible for both SMB and Varicol process.

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