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Author : Jürgen Guddat
Publisher :
ISBN 13 :
Total Pages : 184 pages
Book Rating : 4.3/5 (91 download)
Download or read book Multiobjective and Stochastic Optimization Based on Parametric Optimization written by Jürgen Guddat and published by . This book was released on 1985 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jürgen Guddat
Publisher :
ISBN 13 :
Total Pages : 175 pages
Book Rating : 4.:/5 (916 download)
Download or read book Multiobjective and Stochastic Optimization Based on Parameter Optimization written by Jürgen Guddat and published by . This book was released on 1985 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Collet's Holdings, Ltd. Staff
Publisher :
ISBN 13 : 9780785511816
Total Pages : pages
Book Rating : 4.5/5 (118 download)
Download or read book Multiobjective and Stochastic Optimization Based on Parametric Optimization written by Collet's Holdings, Ltd. Staff and published by . This book was released on 1986 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 175 pages
Book Rating : 4.:/5 (128 download)
Download or read book Mathematical research written by and published by . This book was released on 1985 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Javier Del Ser Lorente
Publisher : BoD – Books on Demand
ISBN 13 : 1789233283
Total Pages : 71 pages
Book Rating : 4.7/5 (892 download)
Download or read book Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization written by Javier Del Ser Lorente and published by BoD – Books on Demand. This book was released on 2018-07-18 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems.
Author : Kurt Marti
Publisher : Springer Science & Business Media
ISBN 13 : 3642558844
Total Pages : 337 pages
Book Rating : 4.6/5 (425 download)
Download or read book Dynamic Stochastic Optimization written by Kurt Marti and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective and constraint functions of dynamic stochastic optimization problems have the form of multidimensional integrals of rather involved in that may have a nonsmooth and even discontinuous character - the tegrands typical situation for "hit-or-miss" type of decision making problems involving irreversibility ofdecisions or/and abrupt changes ofthe system. In general, the exact evaluation of such functions (as is assumed in the standard optimization and control theory) is practically impossible. Also, the problem does not often possess the separability properties that allow to derive the standard in control theory recursive (Bellman) equations.
Author : Ursula Sebastian
Publisher :
ISBN 13 :
Total Pages : 109 pages
Book Rating : 4.:/5 (247 download)
Download or read book Linear and Nonlinear Optimization, Stochastic Optimization, Multiobjective Optimization, Parametric Optimization, Stability written by Ursula Sebastian and published by . This book was released on 1989 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jürgen Branke
Publisher : Springer
ISBN 13 : 3540889086
Total Pages : 481 pages
Book Rating : 4.5/5 (48 download)
Download or read book Multiobjective Optimization written by Jürgen Branke and published by Springer. This book was released on 2008-10-18 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.
Author : Shi-Yu Huang
Publisher : Springer Science & Business Media
ISBN 13 : 940092111X
Total Pages : 425 pages
Book Rating : 4.4/5 (9 download)
Download or read book Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty written by Shi-Yu Huang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Operations Research is a field whose major contribution has been to propose a rigorous fonnulation of often ill-defmed problems pertaining to the organization or the design of large scale systems, such as resource allocation problems, scheduling and the like. While this effort did help a lot in understanding the nature of these problems, the mathematical models have proved only partially satisfactory due to the difficulty in gathering precise data, and in formulating objective functions that reflect the multi-faceted notion of optimal solution according to human experts. In this respect linear programming is a typical example of impressive achievement of Operations Research, that in its detenninistic fonn is not always adapted to real world decision-making : everything must be expressed in tenns of linear constraints ; yet the coefficients that appear in these constraints may not be so well-defined, either because their value depends upon other parameters (not accounted for in the model) or because they cannot be precisely assessed, and only qualitative estimates of these coefficients are available. Similarly the best solution to a linear programming problem may be more a matter of compromise between various criteria rather than just minimizing or maximizing a linear objective function. Lastly the constraints, expressed by equalities or inequalities between linear expressions, are often softer in reality that what their mathematical expression might let us believe, and infeasibility as detected by the linear programming techniques can often been coped with by making trade-offs with the real world.
Author : Achim Bachem
Publisher : Springer Science & Business Media
ISBN 13 : 3642469558
Total Pages : 574 pages
Book Rating : 4.6/5 (424 download)
Download or read book Operations Research ’93 written by Achim Bachem and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume contains extended abstracts of talks presented at the 18th Symposium on Operations Research held at the University of Cologne, September 1-3, 1993. The Symposia on Operations Research are the annual meetings of the Gesellschaft fiir Mathematik, Okonometrie und Operations Research (GMOOR), a scientific society providing a link between research and applications in the areas of applied mathematics, economics and operations research. The broad range of interests and scientific activities covered by GMOOR and its members was demonstrated by about 250 talks presented at the 18th Symposium. As in l'ecent years, emphasis was placed on optimization and stochastics, this year with a special focus on combinatorial optimization and discrete mathematics. We appreciate that with sections on parallel and distributed computing and on scientific computing also new fields could be integrated into the scope of the GMOOR. This book contains extended abstracts of most of the papers presented at the con ference. Long versions and full papers of the talks are expected to appear elsewhere in refereed periodicals. The contributions were divided into sixteen sections: (1) Theory of Optimization, (2) Computational Methods of Optimization, (3) Combinatorial Optimization and Dis crete Mathematics, (4) Scientific Computing, (5) Decision Theory, (6) Mathematical Economics and Game Theory, (7) Banking, Finance and Insurance, (8) Econometrics, (9) Macroeconomics and Economic Theory, (10) Stochastics, (11) Production and Lo gistics, (12) System and Control Theory, (13) Routing and Scheduling, (14) Knowledge Based Systems, (15) Information Systems and (16) Parallel and Distributed Compu ting.
Author : Juan Gabriel Segovia-Hernández
Publisher : CRC Press
ISBN 13 : 1351651781
Total Pages : 254 pages
Book Rating : 4.3/5 (516 download)
Download or read book Stochastic Process Optimization using Aspen Plus® written by Juan Gabriel Segovia-Hernández and published by CRC Press. This book was released on 2017-11-01 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 A. Gomez-Fernandez
Publisher : Springer
ISBN 13 : 3540460055
Total Pages : 285 pages
Book Rating : 4.5/5 (44 download)
Download or read book Approximation and Optimization written by Juan A. Gomez-Fernandez and published by Springer. This book was released on 2006-11-14 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kurt Marti
Publisher : Springer
ISBN 13 : 3662462141
Total Pages : 389 pages
Book Rating : 4.6/5 (624 download)
Download or read book Stochastic Optimization Methods written by Kurt Marti and published by Springer. This book was released on 2015-02-21 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines optimization problems that in practice involve random model parameters. It details the computation of robust optimal solutions, i.e., optimal solutions that are insensitive with respect to random parameter variations, where appropriate deterministic substitute problems are needed. Based on the probability distribution of the random data and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into appropriate deterministic substitute problems. Due to the probabilities and expectations involved, the book also shows how to apply approximative solution techniques. Several deterministic and stochastic approximation methods are provided: Taylor expansion methods, regression and response surface methods (RSM), probability inequalities, multiple linearization of survival/failure domains, discretization methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation and gradient procedures and differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods. In particular, it now shows how to apply stochastic optimization methods to the approximate solution of important concrete problems arising in engineering, economics and operations research.
Author : Biswas, Animesh
Publisher : IGI Global
ISBN 13 : 1522583025
Total Pages : 420 pages
Book Rating : 4.5/5 (225 download)
Download or read book Multi-Objective Stochastic Programming in Fuzzy Environments written by Biswas, Animesh and published by IGI Global. This book was released on 2019-03-22 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is frequently observed that most decision-making problems involve several objectives, and the aim of the decision makers is to find the best decision by fulfilling the aspiration levels of all the objectives. Multi-objective decision making is especially suitable for the design and planning steps and allows a decision maker to achieve the optimal or aspired goals by considering the various interactions of the given constraints. Multi-Objective Stochastic Programming in Fuzzy Environments discusses optimization problems with fuzzy random variables following several types of probability distributions and different types of fuzzy numbers with different defuzzification processes in probabilistic situations. The content within this publication examines such topics as waste management, agricultural systems, and fuzzy set theory. It is designed for academicians, researchers, and students.
Author : Vincent Barichard
Publisher : Springer Science & Business Media
ISBN 13 : 3540856455
Total Pages : 296 pages
Book Rating : 4.5/5 (48 download)
Download or read book Multiobjective Programming and Goal Programming written by Vincent Barichard and published by Springer Science & Business Media. This book was released on 2009-01-30 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives the reader an insight into the state of the art in the field of multiobjective (linear, nonlinear and combinatorial) programming, goal programming and multiobjective metaheuristics. The 26 papers describe all relevant trends in this fields of research . They cover a wide range of topics ranging from theoretical investigations to algorithms, dealing with uncertainty, and applications to real world problems such as engineering design, water distribution systems and portfolio selection. The book is based on the papers of the seventh international conference on multiple objective programming and goal programming (MOPGP06).
Author : Kurt Marti
Publisher : Springer Science & Business Media
ISBN 13 : 3540268480
Total Pages : 317 pages
Book Rating : 4.5/5 (42 download)
Download or read book Stochastic Optimization Methods written by Kurt Marti and published by Springer Science & Business Media. This book was released on 2005-12-05 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, 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. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.
Author : Dan Stefanoiu
Publisher : John Wiley & Sons
ISBN 13 : 1848214987
Total Pages : 444 pages
Book Rating : 4.8/5 (482 download)
Download or read book Optimization in Engineering Sciences written by Dan Stefanoiu and published by John Wiley & Sons. This book was released on 2014-12-03 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to present the main metaheuristics and approximate and stochastic methods for optimization of complex systems in Engineering Sciences. It has been written within the framework of the European Union project ERRIC (Empowering Romanian Research on Intelligent Information Technologies), which is funded by the EU’s FP7 Research Potential program and has been developed in co-operation between French and Romanian teaching researchers. Through the principles of various proposed algorithms (with additional references) this book allows the reader to explore various methods of implementation such as metaheuristics, local search and populationbased methods. It examines multi-objective and stochastic optimization, as well as methods and tools for computer-aided decision-making and simulation for decision-making.
