Download or read book Decision Making with Dominance Constraints in Two Stage Stochastic Integer Programming written by Uwe Gotzes and published by Springer Science & Business Media. This book was released on 2009-09-30 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based upon partial orders on the set of real random variables. He illustrates the superiority of the proposed decomposition method over standard solvers for example with numerical experiments with instances from energy investment.
Download or read book Risk Management in Stochastic Integer Programming written by Frederike Neise and published by Springer Science & Business Media. This book was released on 2008-09-25 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author presents two concepts to handle the classic linear mixed-integer two-stage stochastic optimization problem. She describes mean-risk modeling and stochastic programming with first order dominance constraints. Both approaches are applied to optimize the operation of a dispersed generation system.
Download or read book Lectures on Stochastic Programming written by Alexander Shapiro and published by SIAM. This book was released on 2009-01-01 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization problems involving stochastic models occur in almost all areas of science and engineering, such as telecommunications, medicine, and finance. Their existence compels a need for rigorous ways of formulating, analyzing, and solving such problems. This book focuses on optimization problems involving uncertain parameters and covers the theoretical foundations and recent advances in areas where stochastic models are available. Readers will find coverage of the basic concepts of modeling these problems, including recourse actions and the nonanticipativity principle. The book also includes the theory of two-stage and multistage stochastic programming problems; the current state of the theory on chance (probabilistic) constraints, including the structure of the problems, optimality theory, and duality; and statistical inference in and risk-averse approaches to stochastic programming.
Download or read book Stochastic Programming written by Horand Gassmann and published by World Scientific. This book was released on 2013 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows the breadth and depth of stochastic programming applications. All the papers presented here involve optimization over the scenarios that represent possible future outcomes of the uncertainty problems. The applications, which were presented at the 12th International Conference on Stochastic Programming held in Halifax, Nova Scotia in August 2010, span the rich field of uses of these models. The finance papers discuss such diverse problems as longevity risk management of individual investors, personal financial planning, intertemporal surplus management, asset management with benchmarks, dynamic portfolio management, fixed income immunization and racetrack betting. The production and logistics papers discuss natural gas infrastructure design, farming Atlantic salmon, prevention of nuclear smuggling and sawmill planning. The energy papers involve electricity production planning, hydroelectric reservoir operations and power generation planning for liquid natural gas plants. Finally, two telecommunication papers discuss mobile network design and frequency assignment problems.
Download or read book Decomposition Algorithms for Two stage Stochastic Integer Programming written by John H. Penuel and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: Stochastic programming seeks to optimize decision making in uncertain conditions. This type of work is typically amenable to decomposition into first- and second-stage decisions. First-stage decisions must be made now, while second-stage decisions are made after realizing certain future conditions and are typically constrained by first-stage decisions. This work focuses on two stochastic integer programming applications. In Chapter 2, we investigate a two-stage facility location problem with integer recourse. In Chapter 3, we investigate the graph decontamination problem with mobile agents. In both problems, we develop cutting-plane algorithms that iteratively solve the first-stage problem, then solve the second-stage problem and glean information from the second-stage solution with which we refine first-stage decisions. This process is repeated until optimality is reached. If the second-stage problems are linear programs, then duality can be exploited in order to refine first-stage decisions. If the second-stage problems are mixed-integer programs, then we resort to other methods to extract information from the second-stage problem. The applications discussed in this work have mixed-integer second-stage problems, and accordingly we develop specialized cutting-plane algorithms and demonstrate the efficacy of our solution methods.
Download or read book Stochastic Programming written by Gerd Infanger and published by Springer Science & Business Media. This book was released on 2010-11-10 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the Preface... The preparation of this book started in 2004, when George B. Dantzig and I, following a long-standing invitation by Fred Hillier to contribute a volume to his International Series in Operations Research and Management Science, decided finally to go ahead with editing a volume on stochastic programming. The field of stochastic programming (also referred to as optimization under uncertainty or planning under uncertainty) had advanced significantly in the last two decades, both theoretically and in practice. George Dantzig and I felt that it would be valuable to showcase some of these advances and to present what one might call the state-of- the-art of the field to a broader audience. We invited researchers whom we considered to be leading experts in various specialties of the field, including a few representatives of promising developments in the making, to write a chapter for the volume. Unfortunately, to the great loss of all of us, George Dantzig passed away on May 13, 2005. Encouraged by many colleagues, I decided to continue with the book and edit it as a volume dedicated to George Dantzig. Management Science published in 2005 a special volume featuring the “Ten most Influential Papers of the first 50 Years of Management Science.” George Dantzig’s original 1955 stochastic programming paper, “Linear Programming under Uncertainty,” was featured among these ten. Hearing about this, George Dantzig suggested that his 1955 paper be the first chapter of this book. The vision expressed in that paper gives an important scientific and historical perspective to the book. Gerd Infanger
Download or read book Innovations in Information Systems for Business Functionality and Operations Management written by Wang, John and published by IGI Global. This book was released on 2012-04-30 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers the latest research in IS/IT applications related to business and operations management, with contributions in the form of case studies, methodologies, best practices, frameworks, and research"--Provided by publisher.
Download or read book Stochastic Optimization Methods in Finance and Energy written by Marida Bertocchi and published by Springer Science & Business Media. This book was released on 2011-09-15 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents a collection of contributions dedicated to applied problems in the financial and energy sectors that have been formulated and solved in a stochastic optimization framework. The invited authors represent a group of scientists and practitioners, who cooperated in recent years to facilitate the growing penetration of stochastic programming techniques in real-world applications, inducing a significant advance over a large spectrum of complex decision problems. After the recent widespread liberalization of the energy sector in Europe and the unprecedented growth of energy prices in international commodity markets, we have witnessed a significant convergence of strategic decision problems in the energy and financial sectors. This has often resulted in common open issues and has induced a remarkable effort by the industrial and scientific communities to facilitate the adoption of advanced analytical and decision tools. The main concerns of the financial community over the last decade have suddenly penetrated the energy sector inducing a remarkable scientific and practical effort to address previously unforeseeable management problems. Stochastic Optimization Methods in Finance and Energy: New Financial Products and Energy Markets Strategies aims to include in a unified framework for the first time an extensive set of contributions related to real-world applied problems in finance and energy, leading to a common methodological approach and in many cases having similar underlying economic and financial implications. Part 1 of the book presents 6 chapters related to financial applications; Part 2 presents 7 chapters on energy applications; and Part 3 presents 5 chapters devoted to specific theoretical and computational issues.
Download or read book Applications of Stochastic Programming written by Stein W. Wallace and published by SIAM. This book was released on 2005-01-01 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.
Download or read book Two stage Stochastic Integer Programming written by Rüdiger Schultz and published by . This book was released on 1994 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Decision Making Under Uncertainty in Electricity Markets written by Antonio J. Conejo and published by Springer Science & Business Media. This book was released on 2010-09-08 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision Making Under Uncertainty in Electricity Markets provides models and procedures to be used by electricity market agents to make informed decisions under uncertainty. These procedures rely on well established stochastic programming models, which make them efficient and robust. Particularly, these techniques allow electricity producers to derive offering strategies for the pool and contracting decisions in the futures market. Retailers use these techniques to derive selling prices to clients and energy procurement strategies through the pool, the futures market and bilateral contracting. Using the proposed models, consumers can derive the best energy procurement strategies using the available trading floors. The market operator can use the techniques proposed in this book to clear simultaneously energy and reserve markets promoting efficiency and equity. The techniques described in this book are of interest for professionals working on energy markets, and for graduate students in power engineering, applied mathematics, applied economics, and operations research.
Download or read book Adversarial Risk Analysis written by David L. Banks and published by CRC Press. This book was released on 2015-06-30 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Winner of the 2017 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against
Download or read book Mathematics Key Technology for the Future written by Willi Jäger and published by Springer Science & Business Media. This book was released on 2008-04-10 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about the results of a number of projects funded by the BMBF in the initiative "Mathematics for Innovations in Industry and Services". It shows that a broad spectrum of analytical and numerical mathematical methods and programming techniques are used to solve a lot of different specific industrial or services problems. The main focus is on the fact that the mathematics used is not usually standard mathematics or black box mathematics but is specifically developed for specific industrial or services problems. Mathematics is more than a tool box or an ancilarry science for other scientific disciplines or users. Through this book the reader will gain insight into the details of mathematical modeling and numerical simulation for a lot of industrial applications.
Download or read book A two stage stochastic integer programming approach written by and published by . This book was released on 2005 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bilevel Optimization written by Stephan Dempe and published by Springer Nature. This book was released on 2020-11-23 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2019 marked the 85th anniversary of Heinrich Freiherr von Stackelberg’s habilitation thesis “Marktform und Gleichgewicht,” which formed the roots of bilevel optimization. Research on the topic has grown tremendously since its introduction in the field of mathematical optimization. Besides the substantial advances that have been made from the perspective of game theory, many sub-fields of bilevel optimization have emerged concerning optimal control, multiobjective optimization, energy and electricity markets, management science, security and many more. Each chapter of this book covers a specific aspect of bilevel optimization that has grown significantly or holds great potential to grow, and was written by top experts in the corresponding area. In other words, unlike other works on the subject, this book consists of surveys of different topics on bilevel optimization. Hence, it can serve as a point of departure for students and researchers beginning their research journey or pursuing related projects. It also provides a unique opportunity for experienced researchers in the field to learn about the progress made so far and directions that warrant further investigation. All chapters have been peer-reviewed by experts on mathematical optimization.
Download or read book Preference Ambiguity Averse Decision Making Using Robust Optimization and Sensitivity Analysis written by and published by . This book was released on 2021 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, we study decision making with personalized stochastic optimization models. The methods, we propose, develop custom-tailored stochastic optimization models for a specific decision maker, while preserving the robustness of an optimal decision as expressions of the decision maker's attitude towards ambiguity. We present an optimization model using a novel robust preference relationship -- reference-based almost stochastic dominance (RSD). We use decision maker's utility function as a reference to individualize constraints of stochastic dominance. The concept of RSD addresses the two problems in utility-based decision making: (i) ambiguity and inaccuracy in characterizing the decision maker's individual risk attitude, (ii) over-conservativeness of stochastic dominance representing general properties of risk aversion. The RSD rule reveals the maximum dominance level quantifying the robustness of the decision maker's preference between alternative choices. We develop an approximation model using Bernstein polynomials, show the asymptotic convergence of its optimal value and set of optimal solutions to the true counterparts as the degree of Bernstein polynomials increases, and analyze the convergence rate of its feasible region. We next develop a cut-generation algorithm to solve the approximation model. Finally, we further adapt this cut-generation algorithm to seek a valid option most robustly preferable to a random benchmark. The effectiveness and computational complexity of the model are illustrated using a portfolio optimization problem. We study the sensitivity of the personalized stochastic optimization models with regards to risk entangled with the decision maker's ambiguous preference itself. We present a bi-objective stochastic optimization model --expected utility and sensitivity-averse maximization (ESM), incorporating classical risk-aversion and sensitivity analysis with regards to decision maker's preference. Unlike classical sensitivity analysis approaches which are post-analyses after optimization, ESM incorporates sensitivity analysis in the optimization procedure in terms of the second objective function. It thus allows to produce solutions which are both risk-averse in the classical sense and sensitivity-averse with regards to ambiguity in the decision maker's preference. ESM adapts the sensitivity measure (SMU) from the general Bayesian sensitivity analysis to build connection between classical expected utility maximization and the sensitivity aversion. We develop two solution methods of ESM. A mixed-integer reformulation is given for a preference maximizer decision maker, while a linear programming reformulation for a risk-averse decision maker. The effect of ESM is illustrated using a homeland security budget allocation problem.
Download or read book Discrepancy Distances and Scenario Reduction in Two stage Stochastic Integer Programming written by René Henrion and published by . This book was released on 2007 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt:
