Gade Pandu Rangaiah

Multi-objective optimization : techniques and applications in chemical engineering

Introduction (G P Rangaiah) Multi-Objective Optimization Applications in Chemical Engineering (Masuduzzaman & G P Rangaiah) Techniques: Multi-Objective Evolutionary Algorithms: A Review of the State of the Art and Some of Their Applications in Chemical Engineering (A L Jaimes & C A Coello Coello) The Jumping Gene Adaptations of Multi-Objective Genetic Algorithm and Simulated Annealing (M Ramteke & S K Gupta) Multi-Objective Optimization Using Surrogate-Assisted Evolutionary Algorithm (T Ray) Why Use Interactive Multi-Objective Optimization in Chemical Process Design? (K Miettinen & J Hakanen) Net Flow and Rough Set: Two Methods for Ranking the Pareto Domain (J Thibault) Applications: Multi-Objective Optimization of Gas-Phase Refrigeration Systems for LNG (N Shah et al.) A Multi-Objective Evolutionary Algorithm for Practical Residue Catalytic Cracking Feed Optimization (K C Tan et al.) Optimal Design of Chemical Processes for Multiple Economic and Environmental Objectives (E S Q Lee et al.) Multi-Objective Emergency Response Optimization around Chemical Plants (P S Georgiadou et al.) Array Informatics Using Multi-Objective Genetic Algorithms: From Gene Expressions to Gene Networks (S Garg) Multi-Objective Optimization of a Multi-Product Microbial Cell Factory for Multiple Objectives - A Paradigm for Metabolic Pathway Recipe (F C Lee et al.).

Tabu search for global optimization of continuous functions with application to phase equilibrium calculations

Abstract Tabu (or taboo) search (TS) has been successfully applied to combinatorial optimization but it has not been used for global optimization of many continuous functions including phase equilibrium calculations via Gibbs free energy minimization. In this study, a version of TS, namely, enhanced continuous TS (ECTS), is first tried for benchmark test functions having multiple minima and then evaluated for phase equilibrium calculations. Examples for the latter involve several components, typical conditions and common thermodynamic models. Performance of ECTS is compared with a genetic algorithm (GA). The results show that both TS and GA have high reliability in locating the global minimum, and that TS converges faster than GA thus reducing the computational time and number of function evaluations.

Multiobjective optimization of an industrial styrene reactor

The paper describes a multiobjective optimization study for industrial styrene reactors using non-dominated sorting genetic algorithm (NSGA). Several two- and three- objective functions, namely, production, yield and selectivity of styrene, are considered for adiabatic as well as steam-injected styrene reactors. Pareto optimal (a set of equally good) solutions are obtained due to conflicting effect of either ethyl benzene feed temperature or flow rate. The results provide extensive range of optimal operating conditions, from which a suitable operating point can be selected based on the specific requirements in the plant.

A study of differential evolution and tabu search for benchmark, phase equilibrium and phase stability problems

Abstract Phase equilibrium calculations (PEC) and phase stability (PS) problems play a crucial role in the simulation, design and optimization of separation processes such as distillation and extraction. The former involve the global minimization of Gibbs free energy function whereas the latter requires the global minimization of tangent plane distance function (TPDF). In this work, two promising global optimization techniques: differential evolution (DE) and tabu search (TS) have been evaluated and compared, for the first time, for benchmark, PEC and PS problems. A local optimization technique is used at the end of both TS and DE to improve the accuracy of the final solution. Benchmark problems involve 2–20 variables with a few to hundreds of local minima whereas PEC and PS problems consist of multiple components with comparable minima. PEC involves both vapor–liquid, liquid–liquid and vapor–liquid–liquid equilibria with popular thermodynamic models. The results show that DE is more reliable but computationally less efficient compared to TS for benchmark, PEC and PS problems tested.

A study of equation-solving and gibbs free energy minimization methods for phase equilibrium calculations

Phase equilibrium calculations are often involved in the design, simulation, and optimization of chemical processes. Reported methods for these calculations are based on either equation-solving or Gibbs free energy minimization approaches. The main objective of this work is to compare selected methods for these two approaches, in terms of reliability to find the correct solution, computational time, and number of K-value evaluations. For this, four equation-solving and three free minimization methods have been selected and applied to commonly encountered vapour–liquid equilibrium (VLE), liquid–liquid equilibrium (LLE), and vapour–liquid–liquid equilibrium (VLLE) examples involving multiple components and popular thermodynamic models. Detailed results show that the equation-solving method based on the Rachford–Rice formulation accompanied by mean value theorem and Wegsteins projection is reliable and efficient for two-phase equilibrium calculations not having local minima. When there are multiple minima and for three-phase equilibrium, the stochastic method, genetic algorithm (GA) followed by modified simplex method of Nelder and Mead (NM) is more reliable and desirable. Generic programs for numerical methods are ineffective for phase equilibrium calculations. These findings are of interest and value to researchers and engineers working on phase equilibrium calculations and/or developing thermodynamic models for phase behaviour.

Multi-objective optimization in chemical engineering : developments and applications

For reasons both financial and environmental, there is a perpetual need to optimize the design and operating conditions of industrial process systems in order to improve their performance, energy efficiency, profitability, safety and reliability. However, with most chemical engineering application problems having many variables with complex inter-relationships, meeting these optimization objectives can be challenging. This is where Multi-Objective Optimization (MOO) is useful to find the optimal trade-offs among two or more conflicting objectives.

Phase and chemical equilibrium calculations by direct search optimization

Abstract Direct search optimization is applied to Gibbs free energy minimization to determine phase compositions at equilibrium. The method selected is the random search optimization procedure of Luus and Jaakola, which has been shown to be successful for solving difficult global optimization problems. It is implemented in a multipass fashion where the region size for a variable at the beginning of each pass is put equal to the change in that variable in the previous pass. Results obtained with typical examples for vapor–liquid equilibrium and vapor–liquid equilibrium with reaction, where the liquid and vapor phases may be non-ideal, show that the LJ optimization procedure can be used to find very accurately the global minimum in only a few seconds of computation time on a personal computer. The method is easy to use and has high reliability of locating the global optimum, thus providing a useful means of checking the results obtained by other methods.

Plantwide control : recent developments and applications

The use of control systems is necessary for safe and optimal operation of industrial processes in the presence of inevitable disturbances and uncertainties. Plant-wide control (PWC) involves the systems and strategies required to control an entire chemical plant consisting of many interacting unit operations. Over the past 30 years, many tools and methodologies have been developed to accommodate increasingly larger and more complex plants. This book provides a state-of-the-art of techniques for the design and evaluation of PWC systems. Various applications taken from chemical, petrochemical, biofuels and mineral processing industries are used to illustrate the use of these approaches. This book contains 20 chapters organized in the following sections:

A review on global optimization methods for phase equilibrium modeling and calculations

The phase equilibrium modeling for multi-component systems is essential in process systems engineering. In particular, phase stability analysis, Gibbs free energy minimization and estimation of parameters in thermodynamic models are challenging global optimization problems involved in phase equilibrium calculations and modeling for both reactive and non-reactive systems. To date, many significant works have been performed in the area of global optimization, and several algorithms and computational contributions of global optimization have been used for solving these problems; global optimization methods used include both deterministic and stochastic algorithms. To the best of our knowledge, there is no review in the literature that focuses on the global optimization methods and their applications to phase equilibrium modeling and calculations. In this paper, we briefly describe selected deterministic and stochastic optimization algorithms, and then review their use for phase stability analysis, Gibbs free energy minimization and parameter estimation in phase equilibrium models. In short, we provide a general overview of global optimization for modeling and calculating the phase behavior of systems with and without chemical reactions including the prediction of azeotropes and critical points.

An adaptive internal model control strategy for pH neutralization

Abstract An adaptive internal model control strategy that is capable of providing effective and robust control for pH neutralization has been developed. The approach is based on combining the concepts of non-linear internal model control, strong acid equivalent (Wright and Kravaris, 1991, Ind. Engng Chem. Res. 30 , 1561–1572) and a simplified adaptive mechanism (Huberman and Lumer, 1990, IEEE Trans. Circuits Systems 37 , 547–549). The resulting control system is extensively tested via simulation for acid-base neutralization. The results show the excellent capabilities of the proposed method for disturbance rejection, servo control and tolerance to model uncertainty.