Cover -- Contents -- Preface -- Acknowledgements -- Part one: Multiple criteria in agricultural decisions -- Chapter 1. Main features of the multiple criteria decision-making paradigm -- Criticism of the traditional paradigm for decision-making -- Economic versus technological decisions -- Multiple objectives and goals in agricultural economics -- Historical origins of the MCDM paradigm -- Plan of the book -- Suggestions for further reading -- Chapter 2. Some basic concepts -- Attributes, objectives and goals -- Distinction between goals and constraints -- Pareto optimality -- Trade-offs between decision-making criteria -- A first approximation of the main MCDM approaches -- Suggestions for further reading -- Part two: Multiple criteria decision-making techniques -- Chapter 3. Goal programming -- Introductory example for handling multiple criteria in a farm planning model -- The role of deviational variables in goal programming -- Lexicographic goal programming -- Sensitivity analysis ...
This book presents the Multiple Criteria Decision Making (MCDM) paradigm for modelling agricultural decision-making in three parts. The first part, comprising two chapters, is philosophical in nature and deals with the concepts that define the underlying structure of the MCDM paradigm. The second part is the largest part consisting of five chapters, each of which presents the logic of a specific MCDM technique, and demonstrates how it can be used to model a particular decision problem. In the final part, some selected applications of the MCDM techniques to agricultural problems are presented and thus reinforce the development of an understanding of the MCDM paradigm.The book has been designed for use at different levels: as a textbook for final year undergraduate and postgraduate courses in modelling for decision-making; as a manual for researchers and practising modellers; and, as general reference on the application of MCDM techniques. Readers with basic appreciation of algebra and linear programming can easily follow the contents of this book.
This book aims to justify the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making context. It also discusses the development of the TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) with related examples and MATLAB codes. This is the first book devoted to TOPSIS and its fuzzy versions. It presents the use of fuzzy logic as a logic and as an uncertainty theory in the decision-making content and discusses the development of the TOPSIS method in classical and fuzzy context. The book justifies the use of fuzzy logic as an uncertainty theory and provides illustrative examples for each fuzzy TOPSIS extension, along with related MATLAB codes and case studies. This book is for industrial engineers, operations research engineers, systems engineers, and production engineers working in the areas of decision analysis, multi-criteria decision making, and multiple objective optimization.
Here is 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. He has selected co-editors who are at the top of the sub-fields in natural resources: agriculture, fisheries, forestry, and mining. The book covers these areas with contributions from researchers on, among others, modeling natural research problems, quantifying data, and developing algorithms.
One of the main novelties of this book is its establishment of a clear relationship between social and public choice on one hand and multiple criteria decision analysis on the other. This relationship leads to the new concept of Social Multi-Criteria Evaluation (SMCE). SMCE is proposed as a policy framework to integrate different scientific languages, for example, when concerns about civil society and future generations have to be considered along with policy imperatives and market conditions.
This book discusses policy strategies for the effective management of natural resources in Africa within the context of the United Nations’ Sustainable Development Goals (SDG). While natural resource wealth has the potential to lift many out of poverty, sustain economic growth, and foster political stability, it does not guarantee these benefits. The absolute levels of human development in many resource-rich countries remain low, despite their apparent wealth. The challenge is to adopt policies that better harness the potential of natural resources, not only as an opportunity for development, but also to foster policies and institutional innovations that manage resource wealth equitably and boost human capital. To this end, this volume highlights key opportunities and solutions for harnessing natural resources for sustained economic development and explain how such approaches should be incorporated into the SDG agenda. These opportunities are communicated in the form of policy recommendations that in some cases, are country specific but can (and should) be adapted by individual African countries where applicable. With a broad perspective supplied by a diverse group of authors, this book will be useful for graduate students and academicians studying Africa, development economics, economic policy, and resource management, as well as policy makers, NGOs, and IGOs.
The field of multiple criteria decision analysis (MCDA), also termed multiple criteria decision aid, or multiple criteria decision making (MCDM), has developed rapidly over the past quarter century and in the process a number of divergent schools of thought have emerged. This can make it difficult for a new entrant into the field to develop a comprehensive appreciation of the range of tools and approaches which are available to assist decision makers in dealing with the ever-present difficulties of seeking compromise or consensus between conflicting inter ests and goals, i.e. the "multiple criteria". The diversity of philosophies and models makes it equally difficult for potential users of MCDA, i.e. management scientists and/or decision makers facing problems involving conflicting goals, to gain a clear understanding of which methodologies are appropriate to their particular context. Our intention in writing this book has been to provide a compre hensive yet widely accessible overview of the main streams of thought within MCDA. We aim to provide readers with sufficient awareness of the underlying philosophies and theories, understanding of the practi cal details of the methods, and insight into practice to enable them to implement any of the approaches in an informed manner. As the title of the book indicates, our emphasis is on developing an integrated view of MCDA, which we perceive to incorporate both integration of differ ent schools of thought within MCDA, and integration of MCDA with broader management theory, science and practice.
In two volumes, this new edition presents the state of the art in Multiple Criteria Decision Analysis (MCDA). Reflecting the explosive growth in the field seen during the last several years, the editors not only present surveys of the foundations of MCDA, but look as well at many new areas and new applications. Individual chapter authors are among the most prestigious names in MCDA research, and combined their chapters bring the field completely up to date. Part I of the book considers the history and current state of MCDA, with surveys that cover the early history of MCDA and an overview that discusses the “pre-theoretical” assumptions of MCDA. Part II then presents the foundations of MCDA, with individual chapters that provide a very exhaustive review of preference modeling, along with a chapter devoted to the axiomatic basis of the different models that multiple criteria preferences. Part III looks at outranking methods, with three chapters that consider the ELECTRE methods, PROMETHEE methods, and a look at the rich literature of other outranking methods. Part IV, on Multiattribute Utility and Value Theories (MAUT), presents chapters on the fundamentals of this approach, the very well known UTA methods, the Analytic Hierarchy Process (AHP) and its more recent extension, the Analytic Network Process (ANP), as well as a chapter on MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique). Part V looks at Non-Classical MCDA Approaches, with chapters on risk and uncertainty in MCDA, the decision rule approach to MCDA, the fuzzy integral approach, the verbal decision methods, and a tentative assessment of the role of fuzzy sets in decision analysis. Part VI, on Multiobjective Optimization, contains chapters on recent developments of vector and set optimization, the state of the art in continuous multiobjective programming, multiobjective combinatorial optimization, fuzzy multicriteria optimization, a review of the field of goal programming, interactive methods for solving multiobjective optimization problems, and relationships between MCDA and evolutionary multiobjective optimization (EMO). Part VII, on Applications, selects some of the most significant areas, including contributions of MCDA in finance, energy planning problems, telecommunication network planning and design, sustainable development, and portfolio analysis. Finally, Part VIII, on MCDM software, presents well known MCDA software packages.
