This book considers the problem of determining how many barrels of crude oil an oil-producing and exporting country should produce annually for export―along with several other important problems that decision-makers in the crude oil industry face―and discusses procedures for finding optimum solutions for them. It considers the important Objective Functions they need in making these critical decisions, and discusses procedures to find the best solutions. Outputs from the treatment units, in an oil refinery are only semi-finished products; these are blended into finished products like gasoline, diesel oil, etc., meeting various specifications that the marketplace demands. The book discusses models for solving these problems optimally with examples.
The book provides insights in the decision-making for implementing strategies in various spheres of real-world issues. It integrates optimal policies in various decisionmaking problems and serves as a reference for researchers and industrial practitioners. Furthermore, the book provides sound knowledge of modelling of real-world problems and solution procedure using the various optimisation and statistical techniques for making optimal decisions. The book is meant for teachers, students, researchers and industrialists who are working in the field of materials science, especially operations research and applied statistics.
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.
This global encyclopedic work serves as a comprehensive collection of global scholarship regarding the vast fields of public administration, public policy, governance, and management. Written and edited by leading international scholars and practitioners, this exhaustive resource covers all areas of the above fields and their numerous subfields of study. In keeping with the multidisciplinary spirit of these fields and subfields, the entries make use of various theoretical, empirical, analytical, practical, and methodological bases of knowledge. Expanded and updated, the second edition includes over a thousand of new entries representing the most current research in public administration, public policy, governance, nonprofit and nongovernmental organizations, and management covering such important sub-areas as: 1. organization theory, behavior, change and development; 2. administrative theory and practice; 3. Bureaucracy; 4. public budgeting and financial management; 5. public economy and public management 6. public personnel administration and labor-management relations; 7. crisis and emergency management; 8. institutional theory and public administration; 9. law and regulations; 10. ethics and accountability; 11. public governance and private governance; 12. Nonprofit management and nongovernmental organizations; 13. Social, health, and environmental policy areas; 14. pandemic and crisis management; 15. administrative and governance reforms; 16. comparative public administration and governance; 17. globalization and international issues; 18. performance management; 19. geographical areas of the world with country-focused entries like Japan, China, Latin America, Europe, Asia, Africa, the Middle East, Russia and Eastern Europe, North America; and 20. a lot more. Relevant to professionals, experts, scholars, general readers, researchers, policy makers and manger, and students worldwide, this work will serve as the most viable global reference source for those looking for an introduction and advance knowledge to the field.
Simulations are widely used in the military for training personnel, analyzing proposed equipment, and rehearsing missions, and these simulations need realistic models of human behavior. This book draws together a wide variety of theoretical and applied research in human behavior modeling that can be considered for use in those simulations. It covers behavior at the individual, unit, and command level. At the individual soldier level, the topics covered include attention, learning, memory, decisionmaking, perception, situation awareness, and planning. At the unit level, the focus is on command and control. The book provides short-, medium-, and long-term goals for research and development of more realistic models of human behavior.
Due to inherent limitations in human sensing organs, most data collected for various purposes contain uncertainties. Even at the rare occasions when accurate data are available, the truthful predictions derived on the data tend to create chaotic consequences. So, to effectively process and make sense out of available data, we need methods to deal with uncertainty inherently existing inside the data. The intent of this monograph is to explore the fundamental theory, methods, and techniques of practical application of grey systems theory, initiated by Professor Deng Julong in 1982. This volume presents most of the recent advances of the theory accomplished by scholars from around the world. From studying this book, the reader will not only acquire an overall knowledge of this new theory but also be able to follow the most current research activities. All examples presented are based on practical applications of the theory when urgent real-life problems had to be addressed. Last but not the least, this book concludes with three appendices. The first one compares grey systems theory and interval analysis while revealing the fact that interval analysis is a part of grey mathematics. The second appendix presents an array of different approaches of studying uncertainties. And, the last appendix shows how uncertainties appear using general systems approach.
Asset management is becoming increasingly important to an organization’s strategy, given its effects on cost, production, and quality. No matter the sector, important decisions are made based on techniques and theories that are thought to optimize results; asset management models and techniques could help maximize effectiveness while reducing risk. Optimum Decision Making in Asset Management posits that effective decision making can be augmented by asset management based on mathematical techniques and models. Resolving the problems associated with minimizing uncertainty, this publication outlines a myriad of methodologies, procedures, case studies, and management tools that can help any organization achieve world-class maintenance. This book is ideal for managers, manufacturing engineers, programmers, academics, and advanced management students.
In May 1986, the Association for Behavior Analysis (ABA) established a task force on the right to effective behavioral treatment. The mandate of this task force was to identify and delineate specific rights as they apply to behavioral treatment. Impetus for this project came in part from the controversy over the use of aversive procedures, which some held had no place in treatment and, with evolution of the treatment process, were no longer necessary. In con trast, others cited evidence that programs based on positive reinforcement alone were sometimes not effective in treating severe problems. These re searchers and practitioners desired to ensure that clients and guardians be permitted to choose treatments that included punishment procedures when assessments warranted their use. The first editor approached Ogden Lindsley, president of ABA, about establishing a task force to examine this isuse. The ABA council decided to broaden the mandate to include an examination of clients' right to effective behavioral treatment in general. The first editor was asked to chair the task force and appointed Saul Axelrod, Jon S. Bailey, Judith E. Favell, Richard M. Foxx, and 0. Ivar Lovaas as members. Brian A. Iwata was appointed liaison by the ABA council.
Specifics of Decision Making in Modern Business Systems focuses on the regularities and tendencies that are peculiar for the modern Russian practice of decision making in business systems, as well as the authors’ solutions for its optimization in view of new challenges and possibilities.
