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Author: Juan Gabriel Segovia-Hernández
Publisher: CRC Press
ISBN: 1351651781
Category : Mathematics
Languages : en
Pages : 254
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Book Description
Stochastic Process Optimization using Aspen® Plus Bookshop Category: Chemical Engineering Optimization can be simply defined as "choosing the best alternative among a set of feasible options". In all the engineering areas, optimization has a wide range of applications, due to the high number of decisions involved in an engineering environment. Chemical engineering, and particularly process engineering, is not an exception; thus stochastic methods are a good option to solve optimization problems for the complex process engineering models. In this book, the combined use of the modular simulator Aspen® Plus and stochastic optimization methods, codified in MATLAB, is presented. Some basic concepts of optimization are first presented, then, strategies to use the simulator linked with the optimization algorithm are shown. Finally, examples of application for process engineering are discussed. The reader will learn how to link the process simulator Aspen® Plus and stochastic optimization algorithms to solve process design problems. They will gain ability to perform multi-objective optimization in several case studies. Key Features: • The book links simulation and optimization through numerical analyses and stochastic optimization techniques • Includes use of examples to illustrate the application of the concepts and specific guidance on the use of software (Aspen® Plus, Excel, MATLB) to set up and solve models representing complex problems. • Illustrates several examples of applications for the linking of simulation and optimization software with other packages for optimization purposes. • Provides specific information on how to implement stochastic optimization with process simulators. • Enable readers to identify practical and economic solutions to problems of industrial relevance, enhancing the safety, operation, environmental, and economic performance of chemical processes.
Author: Juan Gabriel Segovia-Hernández
Publisher: CRC Press
ISBN: 1351651781
Category : Mathematics
Languages : en
Pages : 254
Get Book Here
Book Description
Stochastic Process Optimization using Aspen® Plus Bookshop Category: Chemical Engineering Optimization can be simply defined as "choosing the best alternative among a set of feasible options". In all the engineering areas, optimization has a wide range of applications, due to the high number of decisions involved in an engineering environment. Chemical engineering, and particularly process engineering, is not an exception; thus stochastic methods are a good option to solve optimization problems for the complex process engineering models. In this book, the combined use of the modular simulator Aspen® Plus and stochastic optimization methods, codified in MATLAB, is presented. Some basic concepts of optimization are first presented, then, strategies to use the simulator linked with the optimization algorithm are shown. Finally, examples of application for process engineering are discussed. The reader will learn how to link the process simulator Aspen® Plus and stochastic optimization algorithms to solve process design problems. They will gain ability to perform multi-objective optimization in several case studies. Key Features: • The book links simulation and optimization through numerical analyses and stochastic optimization techniques • Includes use of examples to illustrate the application of the concepts and specific guidance on the use of software (Aspen® Plus, Excel, MATLB) to set up and solve models representing complex problems. • Illustrates several examples of applications for the linking of simulation and optimization software with other packages for optimization purposes. • Provides specific information on how to implement stochastic optimization with process simulators. • Enable readers to identify practical and economic solutions to problems of industrial relevance, enhancing the safety, operation, environmental, and economic performance of chemical processes.
Author: José María Ponce-Ortega
Publisher: Springer
ISBN: 3319917226
Category : Technology & Engineering
Languages : en
Pages : 121
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Book Description
This textbook presents a general multi-objective optimization framework for optimizing chemical processes by implementing a link between process simulators and metaheuristic techniques. The proposed approach is general and shows how to implement links between different process simulators such as Aspen Plus®, HYSIS®, Super Pro Designer® linked to a variety of metaheuristic techniques implemented in Matlab®, Excel®, C++, and others, eliminating the numerical complications through the optimization process. Furthermore, the proposed framework allows the use of thermodynamic, design and constitutive equations implemented in the process simulator to implement any process. Aimed at graduate and undergraduate students, it presents introductory chapters for process simulators and metaheuristic optimization techniques and provides several worked exercises as well as proposed exercises. In addition, accompanying tutorial videos clearly explaining the implemented methodologies are available online. Also, some Matlab® routines are included as electronic supporting material.
Author: Mariano Martín Martín
Publisher: CRC Press
ISBN: 0429835434
Category : Computers
Languages : en
Pages : 786
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Book Description
The field of Chemical Engineering and its link to computer science is in constant evolution and new engineers have a variety of tools at their disposal to tackle their everyday problems. Introduction to Software for Chemical Engineers, Second Edition provides a quick guide to the use of various computer packages for chemical engineering applications. It covers a range of software applications from Excel and general mathematical packages such as MATLAB and MathCAD to process simulators, CHEMCAD and ASPEN, equation-based modeling languages, gProms, optimization software such as GAMS and AIMS, and specialized software like CFD or DEM codes. The different packages are introduced and applied to solve typical problems in fluid mechanics, heat and mass transfer, mass and energy balances, unit operations, reactor engineering, process and equipment design and control. This new edition offers a wider view of packages including open source software such as R, Python and Julia. It also includes complete examples in ASPEN Plus, adds ANSYS Fluent to CFD codes, Lingo to the optimization packages, and discusses Engineering Equation Solver. It offers a global idea of the capabilities of the software used in the chemical engineering field and provides examples for solving real-world problems. Written by leading experts, this book is a must-have reference for chemical engineers looking to grow in their careers through the use of new and improving computer software. Its user-friendly approach to simulation and optimization as well as its example-based presentation of the software, makes it a perfect teaching tool for both undergraduate and master levels.
Author: Gade Pandu Rangaiah
Publisher: John Wiley & Sons
ISBN: 1119016304
Category : Technology & Engineering
Languages : en
Pages : 432
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Book Description
The proposed book will be divided into three parts. The chapters in Part I provide an overview of certain aspect of process retrofitting. The focus of Part II is on computational techniques for solving process retrofit problems. Finally, Part III addresses retrofit applications from diverse process industries. Some chapters in the book are contributed by practitioners whereas others are from academia. Hence, the book includes both new developments from research and also practical considerations. Many chapters include examples with realistic data. All these feature make the book useful to industrial engineers, researchers and students.
Author: Gade Pandu Rangaiah
Publisher: World Scientific
ISBN: 9814299200
Category : Technology & Engineering
Languages : en
Pages : 722
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Book Description
Optimization has played a key role in the design, planning and operation of chemical and related processes, for several decades. Global optimization has been receiving considerable attention in the past two decades. Of the two types of techniques for global optimization, stochastic global optimization is applicable to any type of problems having non-differentiable functions, discrete variables and/or continuous variables. It, thus, shows significant promise and potential for process optimization. So far, there are no books focusing on stochastic global optimization and its applications in chemical engineering. Stochastic Global Optimization ? a monograph with contributions by leading researchers in the area ? bridges the gap in this subject, with the aim of highlighting and popularizing stochastic global optimization techniques for chemical engineering applications. The book, with 19 chapters in all, is broadly categorized into two sections that extensively cover the techniques and the chemical engineering applications.
Author: Georg Ch. Pflug
Publisher: Springer
ISBN: 3319088432
Category : Business & Economics
Languages : en
Pages : 309
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Book Description
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.
Author: Chun-hung Chen
Publisher: World Scientific
ISBN: 9814282642
Category : Computers
Languages : en
Pages : 246
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Book Description
With the advance of new computing technology, simulation is becoming very popular for designing large, complex and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be very expensive. Stochastic Simulation Optimization addresses the pertinent efficiency issue via smart allocation of computing resource in the simulation experiments for optimization, and aims to provide academic researchers and industrial practitioners with a comprehensive coverage of OCBA approach for stochastic simulation optimization. Starting with an intuitive explanation of computing budget allocation and a discussion of its impact on optimization performance, a series of OCBA approaches developed for various problems are then presented, from the selection of the best design to optimization with multiple objectives. Finally, this book discusses the potential extension of OCBA notion to different applications such as data envelopment analysis, experiments of design and rare-event simulation.
Author: Stanislav Uryasev
Publisher: Springer Science & Business Media
ISBN: 1475765940
Category : Technology & Engineering
Languages : en
Pages : 438
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Book Description
Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic programming approaches have been successfully used in a number of areas such as energy and production planning, telecommunications, and transportation. Recently, the practical experience gained in stochastic programming has been expanded to a much larger spectrum of applications including financial modeling, risk management, and probabilistic risk analysis. Major topics in this volume include: (1) advances in theory and implementation of stochastic programming algorithms; (2) sensitivity analysis of stochastic systems; (3) stochastic programming applications and other related topics. Audience: Researchers and academies working in optimization, computer modeling, operations research and financial engineering. The book is appropriate as supplementary reading in courses on optimization and financial engineering.
Author: Mahmoud H. Alrefaei
Publisher:
ISBN:
Category :
Languages : en
Pages : 414
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Book Description
Author: Kurt Marti
Publisher: Springer Science & Business Media
ISBN: 9783540222729
Category : Business & Economics
Languages : en
Pages : 332
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Book Description
This text provides a concise overview of stochastic optimization and considers nonlinear optimization problems. Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems.
