Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Mechanism design is an analytical framework for thinking clearly and carefully about what exactly a given institution can achieve when the information necessary to make decisions is dispersed and privately held. This analysis provides an account of the underlying mathematics of mechanism design based on linear programming. Three advantages characterize the approach. The first is simplicity: arguments based on linear programming are both elementary and transparent. The second is unity: the machinery of linear programming provides a way to unify results from disparate areas of mechanism design. The third is reach: the technique offers the ability to solve problems that appear to be beyond solutions offered by traditional methods. No claim is made that the approach advocated should supplant traditional mathematical machinery. Rather, the approach represents an addition to the tools of the economic theorist who proposes to understand economic phenomena through the lens of mechanism design.

Business, Economy and Management --- Economics --- Decision making --- Organizational behavior --- Machine theory. --- Linear programming. --- Mathematical models. --- Abstract automata --- Abstract machines --- Automata --- Mathematical machine theory --- Algorithms --- Logic, Symbolic and mathematical --- Recursive functions --- Robotics --- Behavior in organizations --- Management --- Organization --- Psychology, Industrial --- Social psychology --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management decisions --- Choice (Psychology) --- Problem solving --- Machine theory --- Linear programming --- Mathematical models --- E-books --- Decision making - Linear programming --- Organizational behavior - Mathematical models

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

"Mechanism design is an analytical framework for thinking clearly and carefully about what exactly a given institution can achieve when the information necessary to make decisions is dispersed and privately held. This analysis provides an account of the underlying mathematics of mechanism design based on linear programming. Three advantages characterize the approach. The first is simplicity: arguments based on linear programming are both elementary and transparent. The second is unity: the machinery of linear programming provides a way to unify results from disparate areas of mechanism design. The third is reach: the technique offers the ability to solve problems that appear to be beyond solutions offered by traditional methods. No claim is made that the approach advocated should supplant traditional mathematical machinery. Rather, the approach represents an addition to the tools of the economic theorist who proposes to understand economic phenomena through the lens of mechanism design"

Microeconomics --- Operational research. Game theory --- Decision making --- Organizational behavior --- Machine theory --- Linear programming --- Mathematical models --- Machine theory. --- Linear programming. --- Mathematical models. --- AA / International- internationaal --- 305.6 --- 519.8 --- Risicotheorie, speltheorie. Risicokapitaal. Beslissingsmodellen. --- Operational research --- 519.8 Operational research --- Behavior in organizations --- Management --- Organization --- Psychology, Industrial --- Social psychology --- Abstract automata --- Abstract machines --- Automata --- Mathematical machine theory --- Algorithms --- Logic, Symbolic and mathematical --- Recursive functions --- Robotics --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management decisions --- Choice (Psychology) --- Problem solving --- Risicotheorie, speltheorie. Risicokapitaal. Beslissingsmodellen

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Optimization problems involving uncertain data arise in many areas of industrial and economic applications. Stochastic programming provides a useful framework for modeling and solving optimization problems for which a probability distribution of the unknown parameters is available. Motivated by practical optimization problems occurring in energy systems with regenerative energy supply, Debora Mahlke formulates and analyzes multistage stochastic mixed-integer models. For their solution, the author proposes a novel decomposition approach which relies on the concept of splitting the underlying scenario tree into subtrees. Based on the formulated models from energy production, the algorithm is computationally investigated and the numerical results are discussed.

Mathematical optimization. --- Stochastic approximation. --- Stochastic processes. --- Engineering & Applied Sciences --- Mathematics --- Physical Sciences & Mathematics --- Applied Mathematics --- Mathematical Statistics --- Stochastic programming. --- Mathematics. --- Probabilities. --- Probability Theory and Stochastic Processes. --- Mathematics, general. --- Linear programming --- Distribution (Probability theory. --- Math --- Science --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and methods, including DEA with stochastic outputs modeled via constraints on special risk functions (generalizing chance constraints, ICC’s and CVaR constraints), material on Sharpe-ratio, and Asset Liability Management models involving CVaR in a multi-stage setup. To facilitate use as a text, exercises are included throughout the book, and web access is provided to a student version of the authors’ SLP-IOR software. Additionally, the authors have updated the Guide to Available Software, and they have included newer algorithms and modeling systems for SLP. The book is thus suitable as a text for advanced courses in stochastic optimization, and as a reference to the field. From Reviews of the First Edition: "The book presents a comprehensive study of stochastic linear optimization problems and their applications. … The presentation includes geometric interpretation, linear programming duality, and the simplex method in its primal and dual forms. … The authors have made an effort to collect … the most useful recent ideas and algorithms in this area. … A guide to the existing software is included as well." (Darinka Dentcheva, Mathematical Reviews, Issue 2006 c) "This is a graduate text in optimisation whose main emphasis is in stochastic programming. The book is clearly written. … This is a good book for providing mathematicians, economists and engineers with an almost complete start up information for working in the field. I heartily welcome its publication. … It is evident that this book will constitute an obligatory reference source for the specialists of the field." (Carlos Narciso Bouza Herrera, Zentralblatt MATH, Vol. 1104 (6), 2007).

Electronic books. -- local. --- Linear programming. --- Stochastic processes. --- Linear programming --- Stochastic processes --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Operations Research --- Random processes --- Mathematics. --- Operations research. --- Decision making. --- Applied mathematics. --- Engineering mathematics. --- Mathematical optimization. --- Management science. --- Probabilities. --- Optimization. --- Operations Research, Management Science. --- Appl.Mathematics/Computational Methods of Engineering. --- Probability Theory and Stochastic Processes. --- Operation Research/Decision Theory. --- Applications of Mathematics. --- Probabilities --- Production scheduling --- Programming (Mathematics) --- Distribution (Probability theory. --- Mathematical and Computational Engineering. --- Operations Research/Decision Theory. --- Math --- Science --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Distribution functions --- Frequency distribution --- Characteristic functions --- Engineering --- Engineering analysis --- Mathematical analysis --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Mathematics --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Quantitative business analysis --- Statistical decision --- Decision making

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book develops a complete strategy for decision-making, with the full participation of the decision-maker and utilizing continuous feedback. It introduces the use of the very well-known and proven methodology, linear programming, but specially adapted for this purpose. For this, it incorporates a method to include subjective concepts, as well as the possibility of working with many different and even contradictory objectives. To illustrate the concepts, the book is liberally populated with diverse case studies, such as: -selection between sources of renewable energy -route selection for an oil pipeline project -airport expansion plans -scheduling bridge repairs -housing developments -land use and rehabilitation of abandoned land -selecting construction alternatives for a subway line Taking the reader from the basics to the end of the process, this practical guide will be of interest to anyone undertaking analysis and decision-making on both simple and complex projects, and who is looking for a strategy to organize, classify, and evaluate the large amount of information required to make an informed decision. The strategy includes methods to analyze the results and extract conclusions from them. Readers in the fields of environmental science, engineering, urban-planning, architecture, and business administration will find this book useful.

Environmental management -- Case studies -- Decision making. --- Environmental management -- Decision making. --- Linear programming. --- Multiple criteria decision making -- Case studies. --- Multiple criteria decision making. --- Earth & Environmental Sciences --- Environmental Sciences --- Ecology --- Decision making. --- Balance of nature --- Biology --- Bionomics --- Ecological processes --- Ecological science --- Ecological sciences --- Environment --- Environmental biology --- Oecology --- Decision making with multiple objectives --- MCDM (Decision making) --- Multiattribute decisions --- Multicriteria decision analysis --- Multicriteria decision making --- Multicriteria decision making analysis --- Multiobjective decision making --- Multiple objective decision making --- Environment. --- Management information systems. --- Computer science. --- Matrix theory. --- Algebra. --- Mathematical optimization. --- Engineering economics. --- Engineering economy. --- Environmental sciences. --- Sustainable development. --- Math. Appl. in Environmental Science. --- Engineering Economics, Organization, Logistics, Marketing. --- Management of Computing and Information Systems. --- Linear and Multilinear Algebras, Matrix Theory. --- Sustainable Development. --- Optimization. --- Environmental sciences --- Population biology --- Decision making --- Information Systems. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Development, Sustainable --- Ecologically sustainable development --- Economic development, Sustainable --- Economic sustainability --- ESD (Ecologically sustainable development) --- Smart growth --- Sustainable development --- Sustainable economic development --- Economic development --- Economy, Engineering --- Engineering economics --- Industrial engineering --- Environmental science --- Science --- Environmental aspects --- Mathematics --- Informatics --- Computer-based information systems --- EIS (Information systems) --- Executive information systems --- MIS (Information systems) --- Sociotechnical systems --- Information resources management --- Management --- Communication systems