Operations Research Management Science approaches have helped people for the last 40 years to understand the complex functioning of the systems based upon natural resources, as well as to manage natural resources in the most efficient manner. The areas usually viewed within the natural resources field are: agriculture, fisheries, forestry, and mining and water resources. All of these areas share the common problem of optimally allocating scarcity over a period of time. The scale of time or length of the planning horizon differs from one area to another. We have almost a continuous renewal in the case of the fisheries, periodic cycles in the case of agriculture and forestry and enormous periods of time much beyond the human perception in the case of mining resources. But in all the cases, the critical issue is to obtain an efficient use of the resource along its planned time horizon.
Another element of connection among the different natural resources is due to the interaction between the use of the resource and the environmental impact caused by its extraction or harvest. This type of interaction implies additional complexities in the underlying decision-making process, making the use of OR/MS tools especially relevant.
HANDBOOK OF OPERATIONS RESEARCH IN NATURAL RESOURCES will be the first systematic handbook treatment of quantitative modeling natural resource problems, their allocated efficient use, and societal and economic impact. Andrés Weintraub is the very top person in Natural Resource research. Moreover, he has an international reputation in OR and a former president of the International Federation of Operational Research Societies (IFORS). He has selected co-editors who are at the top of the sub-fields in natural resources: agriculture, fisheries, forestry, and mining. The book will cover these areas in terms with contributions from researchers on modeling natural research problems, quantifying data, developing algorithms, and discussing the benefits of research implementations. The handbook will include tutorial contributions when necessary. Throughout the book, technological advances and algorithmic developments that have been driven by natural resource problems will be called out and discussed.
Algebraic Identification and Estimation Methods in Feedback Control Systems presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws. This book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology. Key features: Presents a radically new approach to online parameter and state estimation. Enables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory. Includes examples in a variety of physical applications with experimental results. Covers the latest developments and applications. Algebraic Identification and Estimation Methods in Feedback Control Systems is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.
This work investigates the time series properties of the unemployment rate of the Spanish regions over the period 1976-2011. For that purpose, the authors employ the PANIC procedures of Bai and Ng (2004), which allows to decompose the observed unemployment rate series into common factor and idiosyncratic components. This enables the authors to identify the exact source behind the hysteretic behaviour found in Spanish regional unemployment. Overall, the analysis with three different proxies for the excess of labour supply renders strong support for the hysteresis hypothesis, which appears to be caused by a common stochastic trend driving all the regional unemployment series. In the second part of the analysis the authors try to determine the macroeconomic and institutional factors that are able to explain the time series evolution of the common factor, and in turn help us shed light on the ultimate sources of hysteresis. The reader shall see how the variables that the empirical analysis emphasises as relevant closely fit into the main causes of the Spanish unemployment behaviour. Finally, some policy considerations drawn from the results are presented.
This monograph provides a novel approach to the evaluation of economic policy by combining two different analytical strategies. On the one hand, the computable general equilibrium (CGE) analysis, a standard tool mostly used to quantify the impact of economic measures or changes in the structural data of the economy. On the other hand, the multiple criteria decision-making (MCDM) approach, an op- misation technique that deals with problems with more than one objective. Ty- cally, CGE is well suited for the analysis of the interactions of multiple agents from the point of view of a planner single objective. Combining this technique with the MCDM approach allows developing models in which we ?nd many interacting agents and a decision maker with several objectives. The contribution of this work is partly methodological and partly applied. It provides a framework for the analysis of this type of problems, as well as a series of applications in which the strength of the approach is made clear. The consideration of environmental problems, as a speci?c ?eld in which this technique of analysis can be used, is particularly well chosen. The environmental concern keeps growing steadily and has already become an issue in most of the standard economic decisions. It is therefore extremely important to ?nd systematic ways to introduce such a concern in the models with which we evaluate the impact of policy measures.