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Book Multiobjective and Stochastic Optimization Based on Parametric Optimization

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:

Book Mathematical research

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:

Book Multiobjective and Stochastic Optimization Based on Parameter Optimization

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:

Book Linear and Nonlinear Optimization  Stochastic Optimization  Multiobjective Optimization  Parametric Optimization  Stability

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:

Book Abstracts

    Book Details:
  • Author : Conference on System Modelling and Optimization
  • Publisher :
  • Release : 1989
  • ISBN :
  • Pages : 169 pages

Download or read book Abstracts written by Conference on System Modelling and Optimization and published by . This book was released on 1989 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Simulation Based Optimization

Download or read book Simulation Based Optimization written by Abhijit Gosavi and published by Springer. This book was released on 2014-10-30 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques – especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: · Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) · Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics · An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters – Static Simulation Optimization, Reinforcement Learning and Convergence Analysis – this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.

Book Fuzzy Stochastic Multiobjective Programming

Download or read book Fuzzy Stochastic Multiobjective Programming written by Masatoshi Sakawa and published by Springer Science & Business Media. This book was released on 2011-02-03 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although studies on multiobjective mathematical programming under uncertainty have been accumulated and several books on multiobjective mathematical programming under uncertainty have been published (e.g., Stancu-Minasian (1984); Slowinski and Teghem (1990); Sakawa (1993); Lai and Hwang (1994); Sakawa (2000)), there seems to be no book which concerns both randomness of events related to environments and fuzziness of human judgments simultaneously in multiobjective decision making problems. In this book, the authors are concerned with introducing the latest advances in the field of multiobjective optimization under both fuzziness and randomness on the basis of the authors’ continuing research works. Special stress is placed on interactive decision making aspects of fuzzy stochastic multiobjective programming for human-centered systems under uncertainty in most realistic situations when dealing with both fuzziness and randomness. Organization of each chapter is briefly summarized as follows: Chapter 2 is devoted to mathematical preliminaries, which will be used throughout the remainder of the book. Starting with basic notions and methods of multiobjective programming, interactive fuzzy multiobjective programming as well as fuzzy multiobjective programming is outlined. In Chapter 3, by considering the imprecision of decision maker’s (DM’s) judgment for stochastic objective functions and/or constraints in multiobjective problems, fuzzy multiobjective stochastic programming is developed. In Chapter 4, through the consideration of not only the randomness of parameters involved in objective functions and/or constraints but also the experts’ ambiguous understanding of the realized values of the random parameters, multiobjective programming problems with fuzzy random variables are formulated. In Chapter 5, for resolving conflict of decision making problems in hierarchical managerial or public organizations where there exist two DMs who have different priorities in making decisions, two-level programming problems are discussed. Finally, Chapter 6 outlines some future research directions.

Book Parametric Optimization and Related Topics III

Download or read book Parametric Optimization and Related Topics III written by Jürgen Guddat and published by Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften. This book was released on 1993 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the proceedings of the third conference on Parametric Optimization and Related Topics, held in Gustrow from 30 August until 5 September, 1991. Parametric optimization, as a part of mathematical programming, investigates the behaviour of solutions to optimization problems under data pertubations. This behaviour, like continuity and differentiability, plays a fundamental role for a series of further questions that are of interest from a practical as well as a theoretical point of view. Many relations to other disciplines of operations research, like stochastic programming, modelbuilding, numerical methods, multiobjective optimization and optimal control, originate from this behaviour. The presented articles (all refereed) are topical and original papers reflecting recent results to current directions of research in theory and applications."

Book Nature inspired Methods for Stochastic  Robust and Dynamic Optimization

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.

Book Operations Research

Download or read book Operations Research written by Günter Fandel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tomas Gal zum 65. Geburtstag

Book Parametric Optimization

Download or read book Parametric Optimization written by Jürgen Guddat and published by . This book was released on 1990-12-21 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores optimization problems in which some or all of the individual data involved depends on one parameter. Beginning with a preliminary survey of solution algorithms in one-parametric optimization, the text moves on to examine the pathfollowing curves of local minimizers, pathfollowing along a connected component in the Karush-Kuhn-Tucker set and in the critical set, pathfollowing in the set of local minimizers and in the set of critical points. In addition, practical applications are included.

Book Stochastic Programming

Download or read book Stochastic Programming written by Horand Gassmann and published by World Scientific. This book was released on 2013 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows the breadth and depth of stochastic programming applications. All the papers presented here involve optimization over the scenarios that represent possible future outcomes of the uncertainty problems. The applications, which were presented at the 12th International Conference on Stochastic Programming held in Halifax, Nova Scotia in August 2010, span the rich field of uses of these models. The finance papers discuss such diverse problems as longevity risk management of individual investors, personal financial planning, intertemporal surplus management, asset management with benchmarks, dynamic portfolio management, fixed income immunization and racetrack betting. The production and logistics papers discuss natural gas infrastructure design, farming Atlantic salmon, prevention of nuclear smuggling and sawmill planning. The energy papers involve electricity production planning, hydroelectric reservoir operations and power generation planning for liquid natural gas plants. Finally, two telecommunication papers discuss mobile network design and frequency assignment problems.

Book Deep Statistical Comparison for Meta heuristic Stochastic Optimization Algorithms

Download or read book Deep Statistical Comparison for Meta heuristic Stochastic Optimization Algorithms written by Tome Eftimov and published by Springer Nature. This book was released on 2022-06-11 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on comprehensive comparisons of the performance of stochastic optimization algorithms, this book provides an overview of the current approaches used to analyze algorithm performance in a range of common scenarios, while also addressing issues that are often overlooked. In turn, it shows how these issues can be easily avoided by applying the principles that have produced Deep Statistical Comparison and its variants. The focus is on statistical analyses performed using single-objective and multi-objective optimization data. At the end of the book, examples from a recently developed web-service-based e-learning tool (DSCTool) are presented. The tool provides users with all the functionalities needed to make robust statistical comparison analyses in various statistical scenarios. The book is intended for newcomers to the field and experienced researchers alike. For newcomers, it covers the basics of optimization and statistical analysis, familiarizing them with the subject matter before introducing the Deep Statistical Comparison approach. Experienced researchers can quickly move on to the content on new statistical approaches. The book is divided into three parts: Part I: Introduction to optimization, benchmarking, and statistical analysis – Chapters 2-4. Part II: Deep Statistical Comparison of meta-heuristic stochastic optimization algorithms – Chapters 5-7. Part III: Implementation and application of Deep Statistical Comparison – Chapter 8.

Book Parametric Optimization and Related Topics

Download or read book Parametric Optimization and Related Topics written by Jürgen Guddat and published by . This book was released on 1987 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Approximation and Optimization

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:

Book Operations Research    93

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.