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Global Optimization of MixedInteger Nonlinear Problems
 AIChE J
"... Two novel deterministic global optimization algorithms for nonconvex mixedinteger problems (MINLPs) are proposed, using the advances of the ffBB algorithm for nonconvex NLPs Adjiman et al. (1998a). The Special Structure MixedInteger ffBB algorithm (SMINffBB addresses problems with nonconvexities ..."
Abstract

Cited by 14 (2 self)
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Two novel deterministic global optimization algorithms for nonconvex mixedinteger problems (MINLPs) are proposed, using the advances of the ffBB algorithm for nonconvex NLPs Adjiman et al. (1998a). The Special Structure MixedInteger ffBB algorithm (SMINffBB addresses problems with nonconvexities in the continuous variables and linear and mixedbilinear participation of the binary variables. The General Structure MixedInteger ffBB algorithm (GMINffBB), is applicable to a very general class of problems for which the continuous relaxation is twice continuously differentiable. Both algorithms are developed using the concepts of branchandbound, but they differ in their approach to each of the required steps. The SMINffBB algorithm is based on the convex underestimation of the continuous functions while the GMINffBB algorithm is centered around the convex relaxation of the entire problem. Both algorithms rely on optimization or interval based variable bound updates to enhance effici...
MixedInteger Nonlinear Optimization in Process Synthesis
, 1998
"... The use of networks allows the representation of a variety of important engineering problems. The treatment of a particular class of network applications, the process synthesis problem, is exposed in this paper. Process Synthesis seeks to develop systematically process flowsheets that convert raw ma ..."
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Cited by 7 (0 self)
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The use of networks allows the representation of a variety of important engineering problems. The treatment of a particular class of network applications, the process synthesis problem, is exposed in this paper. Process Synthesis seeks to develop systematically process flowsheets that convert raw materials into desired products. In recent years, the optimization approach to process synthesis has shown promise in tackling this challenge. It requires the development of a network of interconnected units, the process superstructure, that represents the alternative process flowsheets. The mathematical modeling of the superstructure has a mixed set of binary and continuous variables and results in a mixedinteger optimization model. Due to the nonlinearity of chemical models, these problems are generally classified as MixedInteger Nonlinear Programming (MINLP) problems. A number of local optimization algorithms, developed for the solution of this class of problems, are presented in this pap...
Tabu search algorithm for chemical process optimization
 Computers and Chemical Engineering
, 2004
"... Abstract: This paper presents a metaheuristic optimization algorithm, Tabu Search (TS), and describes how it can be used to solve a wide variety of chemical engineering problems. Modifications to the original algorithm and constraint handling techniques are described and integrated to extend its ap ..."
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Cited by 3 (0 self)
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Abstract: This paper presents a metaheuristic optimization algorithm, Tabu Search (TS), and describes how it can be used to solve a wide variety of chemical engineering problems. Modifications to the original algorithm and constraint handling techniques are described and integrated to extend its applicability. All components of TS are described in detail. Initial values for each key parameter of TS are provided. In addition, guidelines for adjusting these parameters are provided to relieve a significant amount of timeconsuming trialanderror experiments that are typically required with stochastic optimization. Several small NLP and MINLP test cases and three small to middle scale chemical process synthesis problems demonstrate the feasibility and effectiveness of the techniques with recommended parameters. 1.
Solving Heat Exchanger Network Synthesis Problems with Tabu Search
"... Abstract: This paper describes the implementation of a metaheuristic optimization approach, Tabu Search (TS), for Heat Exchanger Networks (HEN) synthesis and compares this approach to others presented in the literature. TS is a stochastic optimization approach that makes use of adaptive memory in t ..."
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Cited by 1 (0 self)
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Abstract: This paper describes the implementation of a metaheuristic optimization approach, Tabu Search (TS), for Heat Exchanger Networks (HEN) synthesis and compares this approach to others presented in the literature. TS is a stochastic optimization approach that makes use of adaptive memory in the form of tabu lists. Both recencybased and frequencybased tabu lists are used to provide shortterm and longterm knowledge of search history. TS is shown to locate the global optima with a high probability and low computation times, demonstrating the algorithmâ€™s potential for solving a variety of other mixed integer nonlinear programming (MINLP) problems. 1.
Nonlinear and MixedInteger Optimization in Chemical Process Network Systems
"... . The use of networks allows the representation of a variety of important engineering problems. The treatment of a particular class of network applications, the Process Synthesis problem, is exposed in this paper. Process Synthesis seeks to develop systematically process flowsheets that convert raw ..."
Abstract
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. The use of networks allows the representation of a variety of important engineering problems. The treatment of a particular class of network applications, the Process Synthesis problem, is exposed in this paper. Process Synthesis seeks to develop systematically process flowsheets that convert raw materials into desired products. In recent years, the optimization approach to process synthesis has shown promise in tackling this challenge. It requires the development of a network of interconnected units, the process superstructure, that represents the alternative process flowsheets. The mathematical modeling of the superstructure has a mixed set of binary and continuous variables and results in a mixedinteger optimization model. Due to the nonlinearity of chemical models, these problems are generally classified as MixedInteger Nonlinear Programming (MINLP) problems. A number of local optimization algorithms for MINLP problems are outlined in this paper: Generalized Benders Decompositi...