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 Business Intelligence written by Carlo Vercellis and published by John Wiley & Sons. This book was released on 2011-08-10 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.

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 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 Anticipatory Optimization for Dynamic Decision Making written by Stephan Meisel and published by Springer Science & Business Media. This book was released on 2011-06-23 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of today’s online information systems rapidly increases the relevance of dynamic decision making within a large number of operational contexts. Whenever a sequence of interdependent decisions occurs, making a single decision raises the need for anticipation of its future impact on the entire decision process. Anticipatory support is needed for a broad variety of dynamic and stochastic decision problems from different operational contexts such as finance, energy management, manufacturing and transportation. Example problems include asset allocation, feed-in of electricity produced by wind power as well as scheduling and routing. All these problems entail a sequence of decisions contributing to an overall goal and taking place in the course of a certain period of time. Each of the decisions is derived by solution of an optimization problem. As a consequence a stochastic and dynamic decision problem resolves into a series of optimization problems to be formulated and solved by anticipation of the remaining decision process. However, actually solving a dynamic decision problem by means of approximate dynamic programming still is a major scientific challenge. Most of the work done so far is devoted to problems allowing for formulation of the underlying optimization problems as linear programs. Problem domains like scheduling and routing, where linear programming typically does not produce a significant benefit for problem solving, have not been considered so far. Therefore, the industry demand for dynamic scheduling and routing is still predominantly satisfied by purely heuristic approaches to anticipatory decision making. Although this may work well for certain dynamic decision problems, these approaches lack transferability of findings to other, related problems. This book has serves two major purposes: ‐ It provides a comprehensive and unique view of anticipatory optimization for dynamic decision making. It fully integrates Markov decision processes, dynamic programming, data mining and optimization and introduces a new perspective on approximate dynamic programming. Moreover, the book identifies different degrees of anticipation, enabling an assessment of specific approaches to dynamic decision making. ‐ It shows for the first time how to successfully solve a dynamic vehicle routing problem by approximate dynamic programming. It elaborates on every building block required for this kind of approach to dynamic vehicle routing. Thereby the book has a pioneering character and is intended to provide a footing for the dynamic vehicle routing community.

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 317 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 The Optimization Edge Reinventing Decision Making to Maximize All Your Company s Assets written by Stephen Sashihara and published by McGraw Hill Professional. This book was released on 2011-02-25 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why downsize when you can OPTIMIZE? "At McDonald’s our focus has always been on providing maximum value to customers through ‘optimal’ quality and tight cost management, which is why Optimization has become such a pivotal concept for us. Steve Sashihara’s book brings the concept to life.” —Kenneth M. Koziol, Corp. Senior Vice President, Innovation and Design, McDonald’s Corp. “Steve Sashihara convincingly demonstrates how the application of advanced quantitative techniques can significantly improve day-to-day decision making, which is what we have done at Quad/Graphics.” —Dave Blais, Executive Vice President, Quad/Graphics “The Optimization Edge is a powerful book that will change the way organizations make decisions and manage their assets.” —Frances Hesselbein, President and CEO, Leader to Leader Institute; Recipient, Presidential Medal of Freedom “At UPS, the ‘optimization edge’ has given us a competitive advantage. It enables us to solve problems of great complexity seamlessly and with increased velocity, resulting in smarter decisions and ultimately bringing greater value to our customers.” —Chuck Holland, Vice President of Industrial Engineering, UPS About the Book: In these challenging economic times, more and more companies have turned to “cut-back management” to ensure their survival. But how do some manage to outshine their competitors—and even grow—during downturns? How does Google outsearch the other search engines? How does McDonald’s McClobber the competition? More important, how can you increase your company’s profits without downsizing? The answer is Asset Optimization. This groundbreaking approach to decision making utilizes the latest advances in mathematics and computer software. Optimization expert Steve Sashihara shows you how to squeeze every ounce of value from your company, even under “perfect storm” conditions. You’ll learn how to: Drive up your company’s value—even in a downturn Re-allocate your resources—for maximum performance Streamline your company—and stay ahead of the competition Optimize your assets—for long-term growth A proven, practical, and workable alternative to “corporate anorexia,” Optimization is your best option for dealing head-on with marketplace volatility and resource scarcity. This step-by-step guide offers concrete, ready-to- use tools drawn from decades of superior business practices—the best-kept secrets of global successes such as Amazon, Google, Marriott, McDonald’s, Intel, SAS, and UPS. You’ll learn what Optimization is, what best practices you can immediately put to use, how to use Optimization to speed up and improve decision making, and how to integrate Optimization into your organization’s culture. If you want to thrive in any economy—and grow your company in the future—forget about downsizing. Get The Optimization Edge.

Download or read book Multiple Criteria Decision Making by Multiobjective Optimization written by Ignacy Kaliszewski and published by Springer. This book was released on 2016-08-02 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook approaches optimization from a multi-aspect, multi-criteria perspective. By using a Multiple Criteria Decision Making (MCDM) approach, it avoids the limits and oversimplifications that can come with optimization models with one criterion. The book is presented in a concise form, addressing how to solve decision problems in sequences of intelligence, modelling, choice and review phases, often iterated, to identify the most preferred decision variant. The approach taken is human-centric, with the user taking the final decision is a sole and sovereign actor in the decision making process. To ensure generality, no assumption about the Decision Maker preferences or behavior is made. The presentation of these concepts is illustrated by numerous examples, figures, and problems to be solved with the help of downloadable spreadsheets. This electronic companion contains models of problems to be solved built in Excel spreadsheet files. Optimization models are too often oversimplifications of decision problems met in practice. For instance, modeling company performance by an optimization model in which the criterion function is short-term profit to be maximized, does not fully reflect the essence of business management. The company’s managing staff is accountable not only for operational decisions, but also for actions which shall result in the company ability to generate a decent profit in the future. This calls for management decisions and actions which ensure short-term profitability, but also maintaining long-term relations with clients, introducing innovative products, financing long-term investments, etc. Each of those additional, though indispensable actions and their effects can be modeled separately, case by case, by an optimization model with a criterion function adequately selected. However, in each case the same set of constraints represents the range of company admissible actions. The aim and the scope of this textbook is to present methodologies and methods enabling modeling of such actions jointly.

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 2009-06-16 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.

Download or read book Business Analytics for Decision Making written by Steven Orla Kimbrough and published by CRC Press. This book was released on 2018-09-03 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business Analytics for Decision Making, the first complete text suitable for use in introductory Business Analytics courses, establishes a national syllabus for an emerging first course at an MBA or upper undergraduate level. This timely text is mainly about model analytics, particularly analytics for constrained optimization. It uses implementations that allow students to explore models and data for the sake of discovery, understanding, and decision making. Business analytics is about using data and models to solve various kinds of decision problems. There are three aspects for those who want to make the most of their analytics: encoding, solution design, and post-solution analysis. This textbook addresses all three. Emphasizing the use of constrained optimization models for decision making, the book concentrates on post-solution analysis of models. The text focuses on computationally challenging problems that commonly arise in business environments. Unique among business analytics texts, it emphasizes using heuristics for solving difficult optimization problems important in business practice by making best use of methods from Computer Science and Operations Research. Furthermore, case studies and examples illustrate the real-world applications of these methods. The authors supply examples in Excel®, GAMS, MATLAB®, and OPL. The metaheuristics code is also made available at the book's website in a documented library of Python modules, along with data and material for homework exercises. From the beginning, the authors emphasize analytics and de-emphasize representation and encoding so students will have plenty to sink their teeth into regardless of their computer programming experience.

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 Practical Financial Optimization written by Stavros A. Zenios and published by Wiley-Blackwell. This book was released on 2008-02-11 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Financial Optimization is a comprehensive guide to optimization techniques in financial decision making. This book illuminates the relationship between theory and practice, providing the readers with solid foundational knowledge. Focuses on classical static mean-variance analysis and portfolio immunization, scenario-based models, multi-period dynamic portfolio optimization, and the relationships between classes of models Analyizes real world applications and implications for financial engineers Includes a list of models and a section on notations that includes a glossary of symbols and abbreviations

Download or read book Optimization Theory Decision Making and Operations Research Applications written by Athanasios Migdalas and published by Springer Science & Business Media. This book was released on 2012-11-28 with total page 364 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 Multicriteria Optimization written by Matthias Ehrgott and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: - Collection of results of multicriteria optimization, including nonlinear, linear and combinatorial optimization problems - Includes numerous illustrations, examples and problems

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 Handbook Of Machine Learning Volume 2 Optimization And Decision Making written by Tshilidzi Marwala and published by World Scientific. This book was released on 2019-11-21 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.