Download or read book Stochastic Dynamic Optimization Models for Societal Resource Allocation written by Armagan Bayram and published by . This book was released on 2014 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study a class of stochastic resource allocation problems that specifically deals with effective utilization of resources in the interest of social value creation. These problems are treated as a separate class of problems mainly due to the nonprofit nature of the application areas, as well as the abstract structure of social value definition. As part of our analysis of these unique characteristics in societal resource allocation, we consider two major application areas involving such decisions. The first application area deals with resource allocations for foreclosed housing acquisitions as part of the response to the foreclosure crisis in the U.S. Two stochastic dynamic models are developed and analyzed for these types of problems. In the first model, we consider strategic resource allocation decisions by community development corporations (CDCs), which aim to minimize the negative effects of foreclosures by acquiring, redeveloping and selling foreclosed properties in their service areas. We model this strategic decision process through different types of stochastic mixed-integer programming formulations, and present alternative solution approaches. We also apply the models to real-world data obtained through interactions with a CDC, and perform both policy related and computational analyses. Based on these analyses, we present some general policy insights involving tradeoffs between different societal objectives, and also discuss the efficiency of exact and heuristic solution approaches for the models. In the second model, we consider a tactical resource allocation problem, and identify socially optimal policies for CDCs in dynamically selecting foreclosed properties for acquisition as they become available over time. The analytical results based on a dynamic programming model are then implemented in a case study involving a CDC, and social return based measures defining selectivity rates at different budget levels are specified. The second application area involves dynamic portfolio management approaches for optimization of surgical team compositions in robotic surgeries. For this problem, we develop a stochastic dynamic model to identify policies for optimal team configurations, where optimality is defined based on the minimum experience level required to achieve the maximum attainable performance over all ranges of feasible experience measures. We derive individual and dependent performance values of each surgical team member by using data on operating room time and team member experience, and then use them as inputs to a stochastic programming based framework that we develop. Several insights and guidelines for dynamic staff allocation to surgical teams are then proposed based on the analytical and numerical results derived from the model.
Download or read book Stochastic Dynamic Programming for Resource Allocation written by Ronnie Johansson and published by . This book was released on 2005 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimization in Economics and Finance written by Bruce D. Craven and published by Springer Science & Business Media. This book was released on 2005 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extends the optimization techniques, in a form that may be adopted for modeling social choice problems. The models in this book provide possible models for a society's social choice for an allocation that maximizes welfare and utilization of resources. A computer program SCOM is presented here for computing social choice models by optimal control.
Download or read book Sustainability And Resources Theoretical Issues In Dynamic Economics written by Mukul Majumdar and published by World Scientific. This book was released on 2020-02-13 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book, Sustainability and Resources: Theoretical Issues in Dynamic Economics, presents a collection of mathematical models dealing with sustainability and resource management.The focus in Part A is on harvesting renewable resources, while Part B explores the optimal extraction of exhaustible resources. Part C introduces models dealing with uncertainty. Some are descriptive models; others have deep roots in intertemporal welfare economics. The tools of dynamic optimization developed in the 1960s are used in a formal, rigorous presentation to address wide-ranging issues that have appeared in academic research as well as policy debates on the world stage.The book also provides a self-contained treatment that is accessible to advanced undergraduate and graduate students, who are interested in dynamic models of resource allocation and social welfare, resource management, and applications of optimization theory and methods of probability theory to economics. For researchers in dynamic economics, it will be an invaluable source for formal treatment of substantive macroeconomic issues raised by policymakers. The part dealing with uncertainty and random dynamical systems (largely developed by the author and his collaborators) exposes the reader to contemporary frontiers of research on stochastic processes with novel applications to economic problems.
Download or read book Stochastic Economics written by Gerhard Tintner and published by Elsevier. This book was released on 2014-05-10 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Economics: Stochastic Processes, Control, and Programming presents some aspects of economics from a stochastic or probabilistic point of view. The application of stochastic processes to the theory of economic development, stochastic control theory, and various aspects of stochastic programming is discussed. Comprised of four chapters, this book begins with a short survey of the stochastic view in economics, followed by a discussion on discrete and continuous stochastic models of economic development. The next chapter focuses on methods of stochastic control and their application to dynamic economic models, with emphasis on those aspects connected especially with the theory of quantitative economic policy. Some basic operational problems of applying stochastic control, particularly in economic systems and organizations for problems such as dynamic resource allocation, growth planning, and economic coordination are considered. The last chapter is devoted to stochastic programming, paying particular attention to the decision rule theory of operations research under the chance-constrained model and a method of incorporating reliability measures into a systems reliability model. This book will be of interest to economists, statisticians, applied mathematicians, operations researchers, and systems engineers.
Download or read book Reinforcement Learning and Stochastic Optimization written by Warren B. Powell and published by John Wiley & Sons. This book was released on 2022-03-15 with total page 1090 pages. Available in PDF, EPUB and Kindle. Book excerpt: REINFORCEMENT LEARNING AND STOCHASTIC OPTIMIZATION Clearing the jungle of stochastic optimization Sequential decision problems, which consist of “decision, information, decision, information,” are ubiquitous, spanning virtually every human activity ranging from business applications, health (personal and public health, and medical decision making), energy, the sciences, all fields of engineering, finance, and e-commerce. The diversity of applications attracted the attention of at least 15 distinct fields of research, using eight distinct notational systems which produced a vast array of analytical tools. A byproduct is that powerful tools developed in one community may be unknown to other communities. Reinforcement Learning and Stochastic Optimization offers a single canonical framework that can model any sequential decision problem using five core components: state variables, decision variables, exogenous information variables, transition function, and objective function. This book highlights twelve types of uncertainty that might enter any model and pulls together the diverse set of methods for making decisions, known as policies, into four fundamental classes that span every method suggested in the academic literature or used in practice. Reinforcement Learning and Stochastic Optimization is the first book to provide a balanced treatment of the different methods for modeling and solving sequential decision problems, following the style used by most books on machine learning, optimization, and simulation. The presentation is designed for readers with a course in probability and statistics, and an interest in modeling and applications. Linear programming is occasionally used for specific problem classes. The book is designed for readers who are new to the field, as well as those with some background in optimization under uncertainty. Throughout this book, readers will find references to over 100 different applications, spanning pure learning problems, dynamic resource allocation problems, general state-dependent problems, and hybrid learning/resource allocation problems such as those that arose in the COVID pandemic. There are 370 exercises, organized into seven groups, ranging from review questions, modeling, computation, problem solving, theory, programming exercises and a “diary problem” that a reader chooses at the beginning of the book, and which is used as a basis for questions throughout the rest of the book.
Download or read book Approximate Dynamic Programming for Dynamic Stochastic Resource Allocation with Applications to Healthcare written by Yasin Gocgun and published by . This book was released on 2010 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Decision Science for Housing and Community Development written by Michael P. Johnson and published by John Wiley & Sons. This book was released on 2015-09-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multidisciplinary approach to problem-solving in community-based organizations using decision models and operations research applications A comprehensive treatment of public-sector operations research and management science, Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities addresses critical problems in urban housing and community development through a diverse set of decision models and applications. The book represents a bridge between theory and practice and is a source of collaboration between decision and data scientists and planners, advocates, and community practitioners. The book is motivated by the needs of community-based organizations to respond to neighborhood economic and social distress, represented by foreclosed, abandoned, and blighted housing, through community organizing, service provision, and local development. The book emphasizes analytic approaches that increase the ability of local practitioners to act quickly, thoughtfully, and effectively. By doing so, practitioners can design and implement responses that reflect stakeholder values associated with healthy and sustainable communities; that benefit from increased organizational capacity for evidence-based responses; and that result in solutions that represent improvements over the status quo according to multiple social outcome measures. Featuring quantitative and qualitative analytic methods as well as prescriptive and exploratory decision modeling, the book also includes: Discussions of the principles of decision theory and descriptive analysis to describe ways to identify and quantify values and objectives for community development Mathematical programming applications for real-world problem solving in foreclosed housing acquisition and redevelopment Applications of case studies and community-engaged research principles to analytics and decision modeling Decision Science for Housing and Community Development: Localized and Evidence-Based Responses to Distressed Housing and Blighted Communities is an ideal textbook for upper-undergraduate and graduate-level courses in decision models and applications; humanitarian logistics; nonprofit operations management; urban operations research; public economics; performance management; urban studies; public policy; urban and regional planning; and systems design and optimization. The book is also an excellent reference for academics, researchers, and practitioners in operations research, management science, operations management, systems engineering, policy analysis, city planning, and data analytics.
Download or read book Optimal Resource Allocation written by Igor A. Ushakov and published by John Wiley & Sons. This book was released on 2013-05-17 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: A UNIQUE ENGINEERING AND STATISTICAL APPROACH TO OPTIMAL RESOURCE ALLOCATION Optimal Resource Allocation: With Practical Statistical Applications and Theory features the application of probabilistic and statistical methods used in reliability engineering during the different phases of life cycles of technical systems. Bridging the gap between reliability engineering and applied mathematics, the book outlines different approaches to optimal resource allocation and various applications of models and algorithms for solving real-world problems. In addition, the fundamental background on optimization theory and various illustrative numerical examples are provided. The book also features: An overview of various approaches to optimal resource allocation, from classical Lagrange methods to modern algorithms based on ideas of evolution in biology Numerous exercises and case studies from a variety of areas, including communications, transportation, energy transmission, and counterterrorism protection The applied methods of optimization with various methods of optimal redundancy problem solutions as well as the numerical examples and statistical methods needed to solve the problems Practical thoughts, opinions, and judgments on real-world applications of reliability theory and solves practical problems using mathematical models and algorithms Optimal Resource Allocation is a must-have guide for electrical, mechanical, and reliability engineers dealing with engineering design and optimal reliability problems. In addition, the book is excellent for graduate and PhD-level courses in reliability theory and optimization.
Download or read book Applications of Stochastic Programming written by Stein W. Wallace and published by SIAM. This book was released on 2005-06-01 with total page 701 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 Optimal Resource Allocation in a Dynamic and Stochastic Environment written by José Niño-Mora and published by . This book was released on 1995 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Optimization Models for Resource Allocation Under Perturbation written by Dongxue Bridgeman and published by . This book was released on 2013 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization Models for Resource allocation are investing in how to make the best use of available but limited resources in order to achieve the best results. In strategic planning, resource allocation is a plan for using available resources, especially in the near future, to achieve the goals of the future. It is a process of allocating resources during the entire planning horizon and among the various units. Resource allocation plans can be decided by using mathematical programming. In this dissertation, the research has been focused on how to allocate resources in the uncertain environment. The mathematical programming formulations for the resource allocation model under severe uncertainty will be studied. In particular, we will focus on solving the stability issues of the traditional probabilistic model. We propose an approach consisting of solving a sequence of convex robust optimization models with unknown-but-bounded random variables along with the stochastic programming to pursue the allocation performance for the expected overall objective value. Our theoretical results show that the proposed approach can always obtain an equivalent or a better expected revenue with the corresponding allocation, while significantly reducing the risk under perturbations. Although this method requires solving two convex mathematical programming models, both models are solved within a timely manner thanks to their convex model instances and with effective, and less, computationally demanding algorithms. With the increasing threats from public health emergencies, such as earthquakes, tornados, pandemic flus, or terrorist attacks, high attention has been paid to the public health response to a pandemic from federal to national level, together with local health departments, and the health-care community. Various organizations cooperate with each other to strengthen the preparedness for the pandemic and disastrous emergencies, thus to improve the public health. The Strategic National Stockpile (SNS) is maintained by the Centers for Disease Control and Prevention (CDC) and the U.S. Department of Health and Human Services (DHHS) for the United States in the event of a shortage of local medical resources or other unanticipated supply problems. The SNS is the United States' national repository of antibiotics, vaccines, chemical antidotes, antitoxins, and other critical medical equipment and supplies. It has the capability to supplement or re-supply local health authorities with necessary materials for relief action within the response time in as little as 12 hours. The pilot study is done with the support of Kentucky SNS to determine the capacity allocation plan for each county in order to maximize the health benefit under various uncertainties, which can never be accurately estimated. We thereby employ a heuristic method named "resource reservation" to suggest the resource allocation plan for Kentucky SNS.
Download or read book Efficient Intertemporal Allocations with Recursive Utility written by Bernard Dumas and published by . This book was released on 1999 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this article, our objective is to determine efficient allocations in economies with multiple agents having recursive utility functions. Our main result is to show that in a multiagent economy, the problem of determining efficient allocations can be characterized in terms of a single value function (that of a social planner), rather than multiple functions (one for each investor), as has been proposed thus far (Duffie, Geoffard and Skiadas (1994)). We then show how the single value function can be identified using the familiar technique of stochastic dynamic programming. We achieve these goals by first extending to a stochastic environment Geoffard's (1996) concept of variational utility and his result that variational utility is equivalent to recursive utility, and then using these results to characterize allocations in a multiagent setting.
Download or read book Resource Allocation Over Time written by Martin J. Beckmann and published by . This book was released on 1972 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Water and Society IV written by C.A. Brebbia and published by WIT Press. This book was released on 2017-08-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents papers from the 4th International Conference on Water & Society. The focus of the conference was to encourage trans-disciplinary communication on issues related to the nature of water, and its use and exploitation by society. The valuable research contained in this book demonstrates the need to bridge the gap between specialists in physical sciences, biology, environmental sciences and health. The availability of clean and inexpensive water can no longer be taken for granted as the need for water continues to increase due a growing global population. Heavy water consumers such as agriculture and industry often contribute to its contamination. Water distribution networks in urban areas and soiled water collection systems, present serious problems as well as the need to maintain ageing infrastructures. Possible technologically solutions, such as desalination or pumping systems are energy demanding but, as costs rise, the techniques currently developed may need to be re-assessed. The following list covers some of the subjects included in this book: Water resources management; Agribusiness; Water as a human right; Water quality; Water resources contamination; Sanitation and health; Water and disaster management; Policy and legislation; Future water demands; Irrigation and water management; Management of catchments; Groundwater management and conservation.
Download or read book Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-03-06 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Office of the Under Secretary of Defense (Personnel & Readiness), referred to throughout this report as P&R, is responsible for the total force management of all Department of Defense (DoD) components including the recruitment, readiness, and retention of personnel. Its work and policies are supported by a number of organizations both within DoD, including the Defense Manpower Data Center (DMDC), and externally, including the federally funded research and development centers (FFRDCs) that work for DoD. P&R must be able to answer questions for the Secretary of Defense such as how to recruit people with an aptitude for and interest in various specialties and along particular career tracks and how to assess on an ongoing basis service members' career satisfaction and their ability to meet new challenges. P&R must also address larger-scale questions, such as how the current realignment of forces to the Asia-Pacific area and other regions will affect recruitment, readiness, and retention. While DoD makes use of large-scale data and mathematical analysis in intelligence, surveillance, reconnaissance, and elsewhereâ€"exploiting techniques such as complex network analysis, machine learning, streaming social media analysis, and anomaly detectionâ€"these skills and capabilities have not been applied as well to the personnel and readiness enterprise. Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions offers and roadmap and implementation plan for the integration of data analysis in support of decisions within the purview of P&R.
Download or read book Selected Water Resources Abstracts written by and published by . This book was released on 1990 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt:
