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Received September 24, 2001
Accepted November 22, 2001
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
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Global Optimization Methods for Chemical Process Design: Deterministic and Stochastic Approaches
School of Chemical Engineering and Technology, Chonbuk National University, Jeonju 561-756, Korea 1Chemical Engineering Department, University of California Los Angeles, Los Angeles, CA 90095, USA
soochoi@chonbuk.ac.kr
Korean Journal of Chemical Engineering, March 2002, 19(2), 227-232(6)
https://doi.org/10.1007/BF02698406
https://doi.org/10.1007/BF02698406
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Abstract
Process optimization often leads to nonconvex nonlinear programming problems, which may have multiple local optima. There are two major approaches to the identification of the global optimum: deterministic approach and stochastic approach. Algorithms based on the deterministic approach guarantee the global optimality of the obtained solution, but are usually applicable to small problems only. Algorithms based on the stochastic approach, which do not guarantee the global optimality, are applicable to large problems, but inefficient when nonlinear equality constraints are involved. This paper reviews representative deterministic and stochastic global optimization algorithms in order to evaluate their applicability to process design problems, which are generally large, and have many nonlinear equality constraints. Finally, modified stochastic methods are investigated, which use a deterministic local algorithm and a stochastic global algorithm together to be suitable for such problems.
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Floudas CA, Visweswaran V, Comput. Chem. Eng., 14, 1397 (1990)
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Goldberg DE, "Genetic Algorithms in Search, Optimization, and Machine Learning," Addison-Wesley, Reading, MA (1989)
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Konno H, Thach PT, Tuy H, "Optimization on Low Rank Non-convex Structures," Kluwer Academic Publishers, Dordrecht, The Netherlands (1997)
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Soland RM, Management Sci., 17, 759 (1971)
Vaidyanathan R, Elhalwagi M, Comput. Chem. Eng., 18(10), 889 (1994)
