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Author: Victor Tang Publisher: Springer ISBN: 3319630261 Category : Business & Economics Languages : en Pages : 668
Book Description
This book provides a practice-driven, yet rigorous approach to executive management decision-making that performs well even under unpredictable conditions. It explains how executives can employ prescribed engineering design methods to arrive at robust outcomes even when faced with uncontrollable uncertainty. The book presents the paradigm and its main principles in Part I; in Part II it illustrates how to frame a decision situation and how to design the decision so that it will produce its intended behavior. In turn, Part III discusses in detail in situ case studies on executive management decisions. Lastly, Part IV summarizes the book and formulates the key lessons learned.
Author: Nicky J. Welton Publisher: John Wiley & Sons ISBN: 111830540X Category : Mathematics Languages : en Pages : 296
Book Description
In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish interventions that are both effective and cost-effective. Usually a single study will not fully address these issues and it is desirable to synthesize evidence from multiple sources. This book aims to provide a practical guide to evidence synthesis for the purpose of decision making, starting with a simple single parameter model, where all studies estimate the same quantity (pairwise meta-analysis) and progressing to more complex multi-parameter structures (including meta-regression, mixed treatment comparisons, Markov models of disease progression, and epidemiology models). A comprehensive, coherent framework is adopted and estimated using Bayesian methods. Key features: A coherent approach to evidence synthesis from multiple sources. Focus is given to Bayesian methods for evidence synthesis that can be integrated within cost-effectiveness analyses in a probabilistic framework using Markov Chain Monte Carlo simulation. Provides methods to statistically combine evidence from a range of evidence structures. Emphasizes the importance of model critique and checking for evidence consistency. Presents numerous worked examples, exercises and solutions drawn from a variety of medical disciplines throughout the book. WinBUGS code is provided for all examples. Evidence Synthesis for Decision Making in Healthcare is intended for health economists, decision modelers, statisticians and others involved in evidence synthesis, health technology assessment, and economic evaluation of health technologies.
Author: Howard Rachlin Publisher: ISBN: Category : Psychology Languages : en Pages : 312
Book Description
This book views both cognitive and behavioural theories and experiments in an historical and philosophical context. Current theory and practice are presented as part of an ongoing effort to understand voluntary human behaviour with roots as deep as those of western civilization. Cognitive and behavioural approaches are viewed as complementary (rather than competing) descriptions of judgement, decision and choice.
Author: Mausam Publisher: Morgan & Claypool Publishers ISBN: 1608458865 Category : Computers Languages : en Pages : 213
Book Description
Provides a concise introduction to the use of Markov Decision Processes for solving probabilistic planning problems, with an emphasis on the algorithmic perspective. It covers the whole spectrum of the field, from the basics to state-of-the-art optimal and approximation algorithms.
Author: Sofia Dias Publisher: John Wiley & Sons ISBN: 1118647505 Category : Mathematics Languages : en Pages : 484
Book Description
A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question "for this pre-identified population of patients, which treatment is 'best'?" A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.
Author: Vincent A. W. J. Marchau Publisher: Springer ISBN: 3030052524 Category : Business & Economics Languages : en Pages : 408
Book Description
This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work. The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.
Author: Thomas L. Saaty Publisher: Springer Science & Business Media ISBN: 1461472792 Category : Business & Economics Languages : en Pages : 333
Book Description
The Analytic Network Process (ANP), developed by Thomas Saaty in his work on multicriteria decision making, applies network structures with dependence and feedback to complex decision making. This new edition of Decision Making with the Analytic Network Process is a selection of the latest applications of ANP to economic, social and political decisions, and also to technological design. The ANP is a methodological tool that is helpful to organize knowledge and thinking, elicit judgments registered in both in memory and in feelings, quantify the judgments and derive priorities from them, and finally synthesize these diverse priorities into a single mathematically and logically justifiable overall outcome. In the process of deriving this outcome, the ANP also allows for the representation and synthesis of diverse opinions in the midst of discussion and debate. The book focuses on the application of the ANP in three different areas: economics, the social sciences and the linking of measurement with human values. Economists can use the ANP for an alternate approach for dealing with economic problems than the usual mathematical models on which economics bases its quantitative thinking. For psychologists, sociologists and political scientists, the ANP offers the methodology they have sought for some time to quantify and derive measurements for intangibles. Finally the book applies the ANP to provide people in the physical and engineering sciences with a quantitative method to link hard measurement to human values. In such a process, one is able to interpret the true meaning of measurements made on a uniform scale using a unit.
Author: Tsutomu Sasao Publisher: Morgan & Claypool Publishers ISBN: 1627056505 Category : Technology & Engineering Languages : en Pages : 123
Book Description
A zero-suppressed decision diagram (ZDD) is a data structure to represent objects that typically contain many zeros. Applications include combinatorial problems, such as graphs, circuits, faults, and data mining. This book consists of four chapters on the applications of ZDDs. The first chapter by Alan Mishchenko introduces the ZDD. It compares ZDDs to BDDs, showing why a more compact representation is usually achieved in a ZDD. The focus is on sets of subsets and on sum-of-products (SOP) expressions. Methods to generate all the prime implicants (PIs), and to generate irredundant SOPs are shown. A list of papers on the applications of ZDDs is also presented. In the appendix, ZDD procedures in the CUDD package are described. The second chapter by Tsutomu Sasao shows methods to generate PIs and irredundant SOPs using a divide and conquer method. This chapter helps the reader to understand the methods presented in the first chapter. The third chapter by Shin-Ichi Minato introduces the "frontier-based" method that efficiently enumerates certain subsets of a graph. The final chapter by Shinobu Nagayama shows a method to match strings of characters. This is important in routers, for example, where one must match the address information of an internet packet to the proprer output port. It shows that ZDDs are more compact than BDDs in solving this important problem. Each chapter contains exercises, and the appendix contains their solutions. Table of Contents: Preface / Acknowledgments / Introduction to Zero-Suppressed Decision Diagrams / Efficient Generation of Prime Implicants and Irredundant Sum-of-Products Expressions / The Power of Enumeration--BDD/ZDD-Based Algorithms for Tackling Combinatorial Explosion / Regular Expression Matching Using Zero-Suppressed Decision Diagrams / Authors' and Editors' Biographies / Index
Author: Denis Bouyssou Publisher: Springer Science & Business Media ISBN: 1461508436 Category : Business & Economics Languages : en Pages : 551
Book Description
Aiding Decisions With Multiple Criteria: Essays in Honor of Bernard Roy is organized around two broad themes: Graph Theory with path-breaking contributions on the theory of flows in networks and project scheduling, Multiple Criteria Decision Aiding with the invention of the family of ELECTRE methods and methodological contribution to decision-aiding which lead to the creation of Multi-Criteria Decision Analysis (MCDA). Professor Bernard Roy has had considerable influence on the development of these two broad areas. £/LIST£ Part one contains papers by Jacques Lesourne, and Dominique de Werra & Pierre Hansen related to the early career of Bernard Roy when he developed many new techniques and concepts in Graph Theory in order to cope with complex real-world problems. Part two of the book is devoted to Philosophy and Epistemology of Decision-Aiding with contributions from Valerie Belton & Jacques Pictet and Jean-Luis Genard & Marc Pirlot. Part three includes contributions based on Theory and Methodology of Multi-Criteria Decision-Aiding based on a general framework for conjoint measurement that allows intrasitive preferences. Denis Bouyssou & Marc Pirlot; Alexis Tsoukiàs, Patrice Perny & Philippe Vincke; Luis Dias & João Clímaco; Daniel Vanderpooten; Michael Doumpos & Constantin Zopounidis; and Marc Roubens offer a considerable range of examinations of this aspect of MCDA. Part four is devoted to Perference Modeling with contributions from Peter Fishburn; Salvatore Greco, Benedetto Matarazzo & Roman Slowinski; Salem Benferhat, Didier Dubois & Henri Prade; Oscar Franzese & Mark McCord; Bertrand Munier; and Raymond Bisdorff. Part five groups Applications of Multi-Criteria Decision-Aiding, and Carlos Henggeler Antunes, Carla Oliveira & João Clímaco; Carlos Bana e Costa, Manuel da Costa-Lobo, Isabel Ramos & Jean-Claude Vansnick; Yannis Siskos & Evangelos Grigoroudis; Jean-Pierre Brans, Pierre Kunsch & Bertrand Mareschal offer a wide variety of application problems. Finally, Part six includes contributions on Multi-Objective Mathematical Programming from Jacques Teghem, Walter Habenicht and Pekka Korhonen.
Author: Stephen R. Watson
Author: Stephen R. Watson
Author: Victor Tang
Author: Nicky J. Welton
Author: Howard Rachlin
Author: Mausam
Author: Sofia Dias
Author: Vincent A. W. J. Marchau
Author: Thomas L. Saaty
Author: Tsutomu Sasao
Author: Denis Bouyssou