Download or read book Objectives and Multi Objective Decision Making Under Uncertainty written by J. Wilhelm and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Objectives and Multi objective Decision Making Under Uncertainty written by Jochen Wilhelm and published by Springer. This book was released on 1975 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Improving Homeland Security Decisions written by Ali E. Abbas and published by Cambridge University Press. This book was released on 2017-11-02 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are we safer from terrorism today and is our homeland security money well spent? This book offers answers and more.

Download or read book Multi objective Decision Analysis written by Clinton W. Brownley and published by Business Expert Press. This book was released on 2013-03-28 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether managing strategy, operations or products, knowing how to make the best decision in a complex, uncertain business environment is difficult. You might be faced with multiple, competing objectives, which means making trade-offs. To complicate matters, any uncertainty makes it hard to explicitly understand how different objectives will impact potential outcomes. This book will help you face these problems. It provides a decision analysis framework implemented as a simple spreadsheet tool. This multi-objective decision analysis framework helps you to measure trade-offs among objectives and incorporate uncertainties and risk preferences. With this book, you will be able to identify what information is needed to make a decision, define how that information should be combined, and, finally, provide quantifiable evidence to clearly communicate and justify the decision. The process involves minimal overhead and is perfect for busy professionals who need a simple, structured process for making, tracking, and communicating decisions. This process makes decision making more efficient by focusing only on information and factors that are well-defined, measureable, and relevant to the decision at hand. The framework requires clear characterization of a decision, ensuring that it can be traced and is consistent with the intended objectives and organizational values. Using this structured decision-making framework, anyone can consistently make better decisions to gain competitive and strategic advantage.

Download or read book Objectives and Multi objective Decision Making Under Uncertainty written by Gerhard A. Aschinger and published by . This book was released on 1975 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multiobjective Decision Making written by Vira Chankong and published by North-Holland. This book was released on 1983 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multi Objective Decision Making written by Diederik M. Zhou and published by Springer Nature. This book was released on 2022-05-31 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs). First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the available information about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems. Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting. Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.

Download or read book Decisions with Multiple Objectives written by Ralph L. Keeney and published by Cambridge University Press. This book was released on 1993-07 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes how a confused decision maker, who wishes to make a reasonable and responsible choice among alternatives, can systematically probe their thoughts and feelings in order to make the critically important trade-offs between incommensurable objectives.

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 Uncertain Multi Attribute Decision Making written by Zeshui Xu and published by Springer. This book was released on 2015-02-05 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces methods for uncertain multi-attribute decision making including uncertain multi-attribute group decision making and their applications to supply chain management, investment decision making, personnel assessment, redesigning products, maintenance services, military system efficiency evaluation. Multi-attribute decision making, also known as multi-objective decision making with finite alternatives, is an important component of modern decision science. The theory and methods of multi-attribute decision making have been extensively applied in engineering, economics, management and military contexts, such as venture capital project evaluation, facility location, bidding, development ranking of industrial sectors and so on. Over the last few decades, great attention has been paid to research on multi-attribute decision making in uncertain settings, due to the increasing complexity and uncertainty of supposedly objective aspects and the fuzziness of human thought. This book can be used as a reference guide for researchers and practitioners working in e.g. the fields of operations research, information science, management science and engineering. It can also be used as a textbook for postgraduate and senior undergraduate students.

Download or read book Multi objective Decision making Under Uncertainty Fuzzy Logic Methods written by Terry L. Hardy and published by . This book was released on 1994 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Interactive Multiobjective Decision Making Under Uncertainty written by Hitoshi Yano and published by CRC Press. This book was released on 2017-02-03 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, many books on multiobjective programming have been published. However, only a few books have been published, in which multiobjective programming under the randomness and the fuzziness are investigated. On the other hand, several books on multilevel programming have been published, in which multiple decision makers are involved in hierarchical decision situations. In this book, we introduce the latest advances in the field of multiobjective programming and multilevel programming under uncertainty. The reader can immediately use proposed methods to solve multiobjective programming and multilevel programming, which are based on linear programming or convex programming technique. Organization of each capter is summarized as follows. In Chapter 2, multiobjective programming problems with random variables are formulated, and the corresponding interactive algorithms are developed to obtain a satisfactory solution, in which the fuzziness of human's subjective judgment for permission levels are considered. In Chapter 3, multiobjective programming problems with fuzzy random variables are formulated, and the corresponding interactive algorithms are developed to obtain a satisfactory solution, in which not only the uncertainty of fuzzy random variables but also the fuzziness of human's subjective judgment for permission levels are considered. In Chapter 4, multiobjective multilevel programming is discussed, and the interactive algorithms are developed to obtain a satisfactory solution, in which the hierarchical decision structure of multiple decision makers is reflected. In Chapter 5, two kinds of farm planning problems are solved by applying the proposed method, in which cost coefficients of crops are expressed by random variables.

Download or read book Multi objective Decision Processes Under Uncertainty written by Lifei Cheng and published by . This book was released on 2003 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

Download or read book Multiobjective Optimization written by Jürgen Branke and published by Springer. This book was released on 2008-10-18 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.

Download or read book Information Processing and Management of Uncertainty in Knowledge Based Systems Applications written by Jesús Medina and published by Springer. This book was released on 2018-05-29 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).

Download or read book Multiple Objective Decision Making written by Ching-Lai Hwang and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: