Download or read book Advanced Optimization and Decision Making Techniques in Textile Manufacturing written by Anindya Ghosh and published by CRC Press. This book was released on 2019-03-18 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization and decision making are integral parts of any manufacturing process and management system. The objective of this book is to demonstrate the confluence of theory and applications of various types of multi-criteria decision making and optimization techniques with reference to textile manufacturing and management. Divided into twelve chapters, it discusses various multi-criteria decision-making methods such as AHP, TOPSIS, ELECTRE, and optimization techniques like linear programming, fuzzy linear programming, quadratic programming, in textile domain. Multi-objective optimization problems have been dealt with two approaches, namely desirability function and evolutionary algorithm. Key Features Exclusive title covering textiles and soft computing fields including optimization and decision making Discusses concepts of traditional and non-traditional optimization methods with textile examples Explores pertinent single-objective and multi-objective optimizations Provides MATLAB coding in the Appendix to solve various types of multi-criteria decision making and optimization problems Includes examples and case studies related to textile engineering and management
Download or read book Optimization Techniques for Decision Making written by Chakraborty Ashis Kumar and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimization for Decision Making written by Víctor Yepes and published by . This book was released on 2020-10-08 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the current context of the electronic governance of society, both administrations and citizens are demanding greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled "Optimization for Decision Making". These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions, or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization for decision making in a coherent manner.
Download or read book Introduction to Optimization Based Decision Making written by Joao Luis de Miranda and published by CRC Press. This book was released on 2021-12-24 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: The large and complex challenges the world is facing, the growing prevalence of huge data sets, and the new and developing ways for addressing them (artificial intelligence, data science, machine learning, etc.), means it is increasingly vital that academics and professionals from across disciplines have a basic understanding of the mathematical underpinnings of effective, optimized decision-making. Without it, decision makers risk being overtaken by those who better understand the models and methods, that can best inform strategic and tactical decisions. Introduction to Optimization-Based Decision-Making provides an elementary and self-contained introduction to the basic concepts involved in making decisions in an optimization-based environment. The mathematical level of the text is directed to the post-secondary reader, or university students in the initial years. The prerequisites are therefore minimal, and necessary mathematical tools are provided as needed. This lean approach is complemented with a problem-based orientation and a methodology of generalization/reduction. In this way, the book can be useful for students from STEM fields, economics and enterprise sciences, social sciences and humanities, as well as for the general reader interested in multi/trans-disciplinary approaches. Features Collects and discusses the ideas underpinning decision-making through optimization tools in a simple and straightforward manner Suitable for an undergraduate course in optimization-based decision-making, or as a supplementary resource for courses in operations research and management science Self-contained coverage of traditional and more modern optimization models, while not requiring a previous background in decision theory
Download or read book Optimization for Decision Making written by Katta G. Murty and published by Springer Science & Business Media. This book was released on 2010-03-14 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear programming (LP), modeling, and optimization are very much the fundamentals of OR, and no academic program is complete without them. No matter how highly developed one’s LP skills are, however, if a fine appreciation for modeling isn’t developed to make the best use of those skills, then the truly ‘best solutions’ are often not realized, and efforts go wasted. Katta Murty studied LP with George Dantzig, the father of linear programming, and has written the graduate-level solution to that problem. While maintaining the rigorous LP instruction required, Murty's new book is unique in his focus on developing modeling skills to support valid decision making for complex real world problems. He describes the approach as 'intelligent modeling and decision making' to emphasize the importance of employing the best expression of actual problems and then applying the most computationally effective and efficient solution technique for that model.
Download or read book Optimization for Decision Making II written by Víctor Yepes and published by MDPI. This book was released on 2020-11-25 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner.
Download or read book Modern Optimization Methods for Decision Making Under Risk and Uncertainty written by Alexei A. Gaivoronski and published by CRC Press. This book was released on 2023-10-06 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book comprises original articles on topical issues of risk theory, rational decision making, statistical decisions, and control of stochastic systems. The articles are the outcome of a series international projects involving the leading scholars in the field of modern stochastic optimization and decision making. The structure of stochastic optimization solvers is described. The solvers in general implement stochastic quasi-gradient methods for optimization and identification of complex nonlinear models. These models constitute an important methodology for finding optimal decisions under risk and uncertainty. While a large part of current approaches towards optimization under uncertainty stems from linear programming (LP) and often results in large LPs of special structure, stochastic quasi-gradient methods confront nonlinearities directly without need of linearization. This makes them an appropriate tool for solving complex nonlinear problems, concurrent optimization and simulation models, and equilibrium situations of different types, for instance, Nash or Stackelberg equilibrium situations. The solver finds the equilibrium solution when the optimization model describes the system with several actors. The solver is parallelizable, performing several simulation threads in parallel. It is capable of solving stochastic optimization problems, finding stochastic Nash equilibria, and of composite stochastic bilevel problems where each level may require the solution of stochastic optimization problem or finding Nash equilibrium. Several complex examples with applications to water resources management, energy markets, pricing of services on social networks are provided. In the case of power system, regulator makes decision on the final expansion plan, considering the strategic behavior of regulated companies and coordinating the interests of different economic entities. Such a plan can be an equilibrium − a planned decision where a company cannot increase its expected gain unilaterally.
Download or read book Optimization Techniques for Decision making and Information Security written by Vinod Kumar and published by Bentham Science Publishers. This book was released on 2024-05-22 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization Techniques for Decision-making and Information Security is a scholarly compilation that has been edited by experts with specialized knowledge in the fields of decision theory and cybersecurity. Through the synthesis of an extensive array of information, this edited volume presents novel methodologies and approaches that forge a link between the critical domain of information security and the realm of decision-making processes. The publication commences with a fundamental investigation that establishes the theoretical foundations of information security-relevant decision-making models. The subsequent chapters present comprehensive evaluations of real-world applications, showcasing an assortment of optimization techniques. The book offers a wide range of perspectives on the practical implementation of data analysis in various domains, including but not limited to power generation and optimization, solid transportation problems, soft computing techniques, wireless sensor networks, parametric set-valued optimization problems, data aggregation optimization techniques, fuzzy linear programming problems, and nonlinear chaotic systems. The anthology concludes with a comprehensive summary of the most noteworthy observations and ramifications extracted from the projects of all contributors. Key features - Presents a wide variety of sophisticated optimization methodologies - Explores the intricate intersection of decision theory and the safeguarding of confidential information. - Emphasizes effectiveness in improving decision-making processes designed to strengthen information security measures. - Showcases practical examples in different industrial domains through case studies and real-world problems. - Provides guidance and contemplations on strengthening information security environments. - Includes scientific references for advanced reading This book serves as an essential reference for policymakers, researchers, and professionals who are learning about or working in information security roles.
Download or read book Multi criteria Decision Making Methods written by Evangelos Triantaphyllou and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-Criteria Decision Making (MCDM) has been one of the fastest growing problem areas in many disciplines. The central problem is how to evaluate a set of alternatives in terms of a number of criteria. Although this problem is very relevant in practice, there are few methods available and their quality is hard to determine. Thus, the question `Which is the best method for a given problem?' has become one of the most important and challenging ones. This is exactly what this book has as its focus and why it is important. The author extensively compares, both theoretically and empirically, real-life MCDM issues and makes the reader aware of quite a number of surprising `abnormalities' with some of these methods. What makes this book so valuable and different is that even though the analyses are rigorous, the results can be understood even by the non-specialist. Audience: Researchers, practitioners, and students; it can be used as a textbook for senior undergraduate or graduate courses in business and engineering.
Download or read book Algorithms for Decision Making written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2022-08-16 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.
Download or read book Optimal Decision Making in Operations Research and Statistics written by Irfan Ali and published by CRC Press. This book was released on 2021-11-29 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides insights in the decision-making for implementing strategies in various spheres of real-world issues. It integrates optimal policies in various decisionmaking problems and serves as a reference for researchers and industrial practitioners. Furthermore, the book provides sound knowledge of modelling of real-world problems and solution procedure using the various optimisation and statistical techniques for making optimal decisions. The book is meant for teachers, students, researchers and industrialists who are working in the field of materials science, especially operations research and applied statistics.
Download or read book Multiple Objective Decision Making Methods and Applications written by C.-L. Hwang and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision making is the process of selecting a possible course of action from all the available alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision maker (OM) wants to attain more than one objective or goal in selecting the course of action while satisfying the constraints dictated by environment, processes, and resources. Another characteristic of these problems is that the objectives are apparently non commensurable. Mathematically, these problems can be represented as: (1. 1 ) subject to: gi(~) ~ 0, ,', . . . ,. ! where ~ is an n dimensional decision variable vector. The problem consists of n decision variables, m constraints and k objectives. Any or all of the functions may be nonlinear. In literature this problem is often referred to as a vector maximum problem (VMP). Traditionally there are two approaches for solving the VMP. One of them is to optimize one of the objectives while appending the other objectives to a constraint set so that the optimal solution would satisfy these objectives at least up to a predetermined level. The problem is given as: Max f. ~) 1 (1. 2) subject to: where at is any acceptable predetermined level for objective t. The other approach is to optimize a super-objective function created by multiplying each 2 objective function with a suitable weight and then by adding them together.
Download or read book Introduction to Optimization Based Decision Making written by João Luis de Miranda and published by Chapman & Hall/CRC. This book was released on 2021-12-19 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: The large and complex challenges the world is facing, the growing prevalence of huge data sets, and the new and developing ways for addressing them (artificial intelligence, data science, machine learning, etc.), means it is increasingly vital that academics and professionals from across disciplines have a basic understanding of the mathematical underpinnings of effective, optimized decision-making. Without it, decision makers risk being overtaken by those who better understand the models and methods, that can best inform strategic and tactical decisions. Introduction to Optimization-Based Decision-Making provides an elementary and self-contained introduction to the basic concepts involved in making decisions in an optimization-based environment. The mathematical level of the text is directed to the post-secondary reader, or university students in the initial years. The prerequisites are therefore minimal, and necessary mathematical tools are provided as needed. This lean approach is complemented with a problem-based orientation and a methodology of generalization/reduction. In this way, the book can be useful for students from STEM fields, economics and enterprise sciences, social sciences and humanities, as well as for the general reader interested in multi/trans-disciplinary approaches. Features Collects and discusses the ideas underpinning decision-making through optimization tools in a simple and straightforward manner Suitable for an undergraduate course in optimization-based decision-making, or as a supplementary resource for courses in operations research and management science Self-contained coverage of traditional and more modern optimization models, while not requiring a previous background in decision theory
Download or read book Construction Program Management Decision Making and Optimization Techniques written by Ali D. Haidar and published by Springer. This book was released on 2015-09-12 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring complex and intelligent analytical and mathematical methods, this book examines how different approaches can be used to optimize program management in the construction industry. It presents an in-depth study of the different program management methods, ranging from simple decision-making techniques and statistics analysis to the more complex linear programming and demonstrates how knowledge-base systems and genetic algorithms can be used to optimize resources and meet time, budget and quality criteria. It addresses topics including decision-making principles, planning and scheduling, mathematical forecasting models, optimization techniques programming and artificial intelligence techniques. Providing a valuable resource for anyone managing multiple projects in the construction industry, this book is intended for civil and construction engineering students, project managers, construction managers and senior engineers.
Download or read book Optimization Theory Decision Making and Operations Research Applications written by Athanasios Migdalas and published by Springer. This book was released on 2014-12-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: These proceedings consist of 30 selected research papers based on results presented at the 10th Balkan Conference & 1st International Symposium on Operational Research (BALCOR 2011) held in Thessaloniki, Greece, September 22-24, 2011. BALCOR is an established biennial conference attended by a large number of faculty, researchers and students from the Balkan countries but also from other European and Mediterranean countries as well. Over the past decade, the BALCOR conference has facilitated the exchange of scientific and technical information on the subject of Operations Research and related fields such as Mathematical Programming, Game Theory, Multiple Criteria Decision Analysis, Information Systems, Data Mining and more, in order to promote international scientific cooperation. The carefully selected and refereed papers present important recent developments and modern applications and will serve as excellent reference for students, researchers and practitioners in these disciplines.
Download or read book Decision Making and Optimization written by Martin Gavalec and published by Springer. This book was released on 2014-10-08 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a benefit for graduate and postgraduate students in the areas of operations research, decision theory, optimization theory, linear algebra, interval analysis and fuzzy sets. The book will also be useful for the researchers in the respective areas. The first part of the book deals with decision making problems and procedures that have been established to combine opinions about alternatives related to different points of view. Procedures based on pairwise comparisons are thoroughly investigated. In the second part we investigate optimization problems where objective functions and constraints are characterized by extremal operators such as maximum, minimum or various triangular norms (t-norms). Matrices in max-min algebra are useful in applications such as automata theory, design of switching circuits, logic of binary relations, medical diagnosis, Markov chains, social choice, models of organizations, information systems, political systems and clustering. The input data in real problems are usually not exact and can be characterized by interval values.
Download or read book Opportunities in Neuroscience for Future Army Applications written by National Research Council and published by National Academies Press. This book was released on 2009-07-16 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances and major investments in the field of neuroscience can enhance traditional behavioral science approaches to training, learning, and other applications of value to the Army. Neural-behavioral indicators offer new ways to evaluate how well an individual trainee has assimilated mission critical knowledge and skills, and can also be used to provide feedback on the readiness of soldiers for combat. Current methods for matching individual capabilities with the requirements for performing high-value Army assignments do not include neuropsychological, psychophysiological, neurochemical or neurogenetic components; simple neuropsychological testing could greatly improve training success rates for these assignments. Opportunities in Neuroscience for Future Army Applications makes 17 recommendations that focus on utilizing current scientific research and development initiatives to improve performance and efficiency, collaborating with pharmaceutical companies to employ neuropharmaceuticals for general sustainment or enhancement of soldier performance, and improving cognitive and behavioral performance using interdisciplinary approaches and technological investments. An essential guide for the Army, this book will also be of interest to other branches of military, national security and intelligence agencies, academic and commercial researchers, pharmaceutical companies, and others interested in applying the rapid advances in neuroscience to the performance of individual and group tasks.
