Uncertainty, Constraints, and Decision Making

Uncertainty, Constraints, and Decision Making PDF Author: Martine Ceberio
Publisher: Springer Nature
ISBN: 3031363949
Category : Technology & Engineering
Languages : en
Pages : 437

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Book Description
In the first approximation, decision making is nothing else but an optimization problem: We want to select the best alternative. This description, however, is not fully accurate: it implicitly assumes that we know the exact consequences of each decision, and that, once we have selected a decision, no constraints prevent us from implementing it. In reality, we usually know the consequences with some uncertainty, and there are also numerous constraints that needs to be taken into account. The presence of uncertainty and constraints makes decision making challenging. To resolve these challenges, we need to go beyond simple optimization, we also need to get a good understanding of how the corresponding systems and objects operate, a good understanding of why we observe what we observe – this will help us better predict what will be the consequences of different decisions. All these problems – in relation to different application areas – are the main focus of this book.

Uncertainty, Constraints, and Decision Making

Uncertainty, Constraints, and Decision Making PDF Author: Martine Ceberio
Publisher: Springer Nature
ISBN: 3031363949
Category : Technology & Engineering
Languages : en
Pages : 437

Get Book

Book Description
In the first approximation, decision making is nothing else but an optimization problem: We want to select the best alternative. This description, however, is not fully accurate: it implicitly assumes that we know the exact consequences of each decision, and that, once we have selected a decision, no constraints prevent us from implementing it. In reality, we usually know the consequences with some uncertainty, and there are also numerous constraints that needs to be taken into account. The presence of uncertainty and constraints makes decision making challenging. To resolve these challenges, we need to go beyond simple optimization, we also need to get a good understanding of how the corresponding systems and objects operate, a good understanding of why we observe what we observe – this will help us better predict what will be the consequences of different decisions. All these problems – in relation to different application areas – are the main focus of this book.

Decision Making Under Uncertainty and Constraints

Decision Making Under Uncertainty and Constraints PDF Author: Martine Ceberio
Publisher: Springer Nature
ISBN: 3031164156
Category : Technology & Engineering
Languages : en
Pages : 286

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Book Description
This book shows, on numerous examples, how to make decisions in realistic situations when we have both uncertainty and constraints. In most these situations, the book's emphasis is on the why-question, i.e., on a theoretical explanation for empirical formulas and techniques. Such explanations are important: they help understand why these techniques work well in some cases and not so well in others, and thus, help practitioners decide whether a technique is appropriate for a given situation. Example of applications described in the book ranges from science (biosciences, geosciences, and physics) to electrical and civil engineering, education, psychology and decision making, and religion—and, of course, include computer science, AI (in particular, eXplainable AI), and machine learning. The book can be recommended to researchers and students in these application areas. Many of the examples use general techniques that can be used in other application areas as well, so it is also useful for practitioners and researchers in other areas who are looking for possible theoretical explanations of empirical formulas and techniques.

Decision Making under Constraints

Decision Making under Constraints PDF Author: Martine Ceberio
Publisher: Springer Nature
ISBN: 3030408140
Category : Technology & Engineering
Languages : en
Pages : 222

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Book Description
This book presents extended versions of selected papers from the annual International Workshops on Constraint Programming and Decision Making from 2016 to 2018. The papers address all stages of decision-making under constraints: (1) precisely formulating the problem of multi-criteria decision-making; (2) determining when the corresponding decision problem is algorithmically solvable; (3) finding the corresponding algorithms and making these algorithms as efficient as possible; and (4) taking into account interval, probabilistic, and fuzzy uncertainty inherent in the corresponding decision-making problems. In many application areas, it is necessary to make effective decisions under constraints, and there are several area-specific techniques for such decision problems. However, because they are area-specific, it is not easy to apply these techniques in other application areas. As such, the annual International Workshops on Constraint Programming and Decision Making focus on cross-fertilization between different areas, attracting researchers and practitioners from around the globe. The book includes numerous papers describing applications, in particular, applications to engineering, such as control of unmanned aerial vehicles, and vehicle protection against improvised explosion devices.

Decision Making Under Certainty

Decision Making Under Certainty PDF Author: Arthur Schleifer
Publisher: Thomson South-Western
ISBN: 9781565272743
Category : Decision making
Languages : en
Pages : 0

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Book Description
This book is designed to help readers analyze, make economic tradeoffs and choose wisely in complex decision problems where uncertainty, for all practical purposes, can be ignored. The authors focus on decisions involving relevant costs and revenues, pricing, constraints, the time value of money, and the use of scenarios, or what if analysis.

Advances in Decision Making Under Risk and Uncertainty

Advances in Decision Making Under Risk and Uncertainty PDF Author: Mohammed Abdellaoui
Publisher: Springer Science & Business Media
ISBN: 3540684379
Category : Business & Economics
Languages : en
Pages : 246

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Book Description
Brings the reader into contact with the accomplished progress in individual decision making through the contributions to uncertainty modeling and behavioral decision making. This work also introduces the reader to the subtle issues to be resolved for rational choice under uncertainty.

Decision Making Under Uncertainty

Decision Making Under Uncertainty PDF Author: Charles A. Holloway
Publisher: Prentice Hall
ISBN:
Category : Business & Economics
Languages : en
Pages : 560

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Book Description
Introduction and basic concepts; Models and probability; Choices and preferences; Preference assessment procedures; Behavioral assumptions and limitations of decision analysis; Risk sharing and incentives; Choices with multiple attributes.

Decision Making Under Uncertainty

Decision Making Under Uncertainty PDF Author: Claude Greengard
Publisher: Springer Science & Business Media
ISBN: 146849256X
Category : Mathematics
Languages : en
Pages : 166

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Book Description
In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.

Uncertainty and Environmental Decision Making

Uncertainty and Environmental Decision Making PDF Author: Jerzy A. Filar
Publisher: Springer Science & Business Media
ISBN: 1441911294
Category : Science
Languages : en
Pages : 347

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Book Description
The 21st century promises to be an era dominated by international response to c- tain global environmental challenges such as climate change, depleting biodiversity and biocapacity as well as general atmospheric, water and soil pollution problems. Consequently, Environmental decision making (EDM) is a socially important ?eld of development for Operations Research and Management Science (OR/MS). - certainty is an important feature of these decision problems and it intervenes at very different time and space scales. The Handbook on “Uncertainty and Environmental Decision Making” provides a guided tour of selected methods and tools that OR/MS offer to deal with these issues. Below, we brie?y introduce, peer reviewed, chapters of this handbook and the topics that are treated by the invited authors. The ?rst chapter is a general introduction to the challenges of environmental decision making, the use of OR/MS techniques and a range of tools that are used to deal with uncertainty in this domain.

Optimal Decisions Under Uncertainty

Optimal Decisions Under Uncertainty PDF Author: J.K. Sengupta
Publisher: Springer Science & Business Media
ISBN: 3642701639
Category : Business & Economics
Languages : en
Pages : 295

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Book Description
Understanding the stochastic enviornment is as much important to the manager as to the economist. From production and marketing to financial management, a manager has to assess various costs imposed by uncertainty. The economist analyzes the role of incomplete and too often imperfect information structures on the optimal decisions made by a firm. The need for understanding the role of uncertainty in quantitative decision models, both in economics and management science provide the basic motivation of this monograph. The stochastic environment is analyzed here in terms of the following specific models of optimization: linear and quadratic models, linear programming, control theory and dynamic programming. Uncertainty is introduced here through the para meters, the constraints, and the objective function and its impact evaluated. Specifically recent developments in applied research are emphasized, so that they can help the decision-maker arrive at a solution which has some desirable charac teristics like robustness, stability and cautiousness. Mathematical treatment is kept at a fairly elementary level and applied as pects are emphasized much more than theory. Moreover, an attempt is made to in corporate the economic theory of uncertainty into the stochastic theory of opera tions research. Methods of optimal decision rules illustrated he re are applicable in three broad areas: (a) applied economic models in resource allocation and economic planning, (b) operations research models involving portfolio analysis and stochastic linear programming and (c) systems science models in stochastic control and adaptive behavior.

Modern Optimization Methods for Decision Making Under Risk and Uncertainty

Modern Optimization Methods for Decision Making Under Risk and Uncertainty PDF Author: Alexei A. Gaivoronski
Publisher: CRC Press
ISBN: 1000983927
Category : Computers
Languages : en
Pages : 388

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Book Description
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.