Tabu Search Applications in the Chemical Industry (by Bao Lin)
TS has seen increasing applications in the chemical industry, where most optimization problems are
nonlinear in either the objective function or constraints and often involve both continuous and discrete
variables, resulting in mixed-integer linear/non-linear programming (MILP/MINLP) problems. Wang et al.,
[1] and Calvin et. al. [2] applied the TS approach to the optimal design of chemical processes. TS was
utilized for phase equilibrium calculations via Gibbs free energy minimization [3-4]. Comparing to GA, TS
converged faster thus reducing the computational time and the number of function evaluations. Lin and
Miller [5] reported the application of TS to the pump system configuration problem. The objective is to
determine the most cost-effective configuration of a pump system that can achieve a specified pressure rise.
As energy costs continue to increase, industry will have greater incentive to apply heat integration as
broadly as possible in their facilities. TS was reported in [5-6] for Heat Exchanger Network (HEN)
synthesis problems to minimize the annualized cost. TS located the global optimum with high probability.
In addition, these studies established that the TS algorithm can be readily applied to a variety of problems
without the need for extensive analysis and reformulation.
Computer Aided Molecular Design (CAMD) techniques have been developed to reduce the time and cost
of trial-and-error experiments by identifying promising candidate molecules based on predicted properties.
The TS algorithm implemented with novel neighbor-generating operators and combined with property
prediction via connectivity index-based correlations provides a powerful technique for generating lists of
near-optimal molecular candidates for given applications [7-8]. Lin et. al. [9] presented the formulation of
optimal component lumping problems to minimize the loss of information. The original problem is
reformulated such that the number of independent variables is significantly reduced. Case studies
demonstrate that the reformulated optimal lumping problem can be efficiently solved with the TS approach.
With the increasing availability of multi-core processors and networks of workstations, a growing number
of users will find parallel computing a cost effective approach to solving larger and more complex
problems. Lin and Miller [10] described strategies for parallelizing TS code, with OpenMP, MPI and a
hybrid models, as well as the detailed implementation on personal computer and clusters.
Since all mathematical formulations are obtained through simplifications and have limited accuracy, the
determination of the global optimum is often not as critical as finding a set of near-optimal solutions. The
ability of TS to efficiently locate a set of near-optimal solutions is particularly useful for optimization
problems in chemical industry.
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in a multipurpose plant using Tabu Search with a design-space diversification.
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functions with application to phase equilibrium calculations. Computers and
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Srinivas, M. and G.P. Rangaiah, A study of differential evolution and tabu search
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Lin, B. and D.C. Miller, Solving Heat Exchanger Network Synthesis Problems
with Tabu Search. Computers & Chemical Engineering, 2004. 28(8): p. 14511464.
Lin, B., S. Chavali, K. Camarda, and D.C. Miller, Computer-aided molecular
design using Tabu search. Computers and Chemical Engineering, 2005. 29: p.
337-347.
Chavali, S., B. Lin, D.C. Miller, and K.V. Camardaa, Environmentally-benign
transition metal catalyst design using optimization techniques. Comp. Chem.
Engng., 2004. 28: p. 605-611.
Lin, B., C.F. Leibovici, and S.B. Jørgensen, Optimal component lumping :
Problem formulation and solution techniques. Comp. Chem. Engng., 2008. 32: p.
1167-1172.
Lin, B. and D.C. Miller, Schemes and Implementations of Parallel Stochastic
Optimization Algorithms: Application of Tabu Search to Chemical Engineering
Problems, in STOCHASTIC GLOBAL OPTIMIZATION: Techniques and
Applications in Chemical Engineering, G.P. Rangaiah, Editor. 2010, World
Scientific.