Cross Disciplinary Analyses Using Multi Attribute Utility Theory
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Cross-disciplinary Analyses Using Multi-attribute Utility Theory
This dissertation consists of three projects that apply multi-attribute utility theory to contexts in which there are unique structural relationships between the attributes. In the first project, we develop an initial model for maximizing expected utility in health decisions, based on the principles of quality-adjusted life years (QALY). We then extend this model to allow for adaptation to health states. We do this by maintaining a reference level for each possible health condition being considered. A particular formulation of the utility function and reference levels allows us to compute the a priori reference-dependent expected utility for any given alternative. In the second project, we develop preference conditions for decisions made using Geographic Information Systems (GIS). These conditions allow us to simplify the elicitation of preferences over spatially-defined outcomes, and are based on standard results in multi-attribute utility theory. We then apply these tools to several specific decisions, in the contexts of urban development, irrigation, nuclear accident planning, and fire coverage. In the third project, we formulate and develop utility structures that can effectively incorporate altruistic preferences. Specifically, we examine the utility implications of multiple individuals having altruistic tendencies toward one another. We explore utility structures with two altruistic individuals, and then expand our results to a more general model. The more general model can be greatly simplified by dividing the altruistic individuals up into groups, wherein the altruistic interactions are expressed at the group level. Our results can be expanded beyond altruism; they provide insight for any situation in which each individual outcome includes externalities that affect the outcomes experienced by others.
Multiple Criteria Decision Analysis
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.
Location Theory and Decision Analysis
Author: Yupo Chan
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-08-26
Employing state-of-the art quantitative models and case studies, Location Theory and Decision Analysis provides the methodologies behind the siting of such facilities as transportation terminals, warehouses, housing, landfills, state parks and industrial plants. Through its extensive methodological review, the book serves as a primer for more advanced texts on spatial analysis, including the monograph on Location, Transport and Land-Use by the same author. Given the rapid changes over the last decade, the Second Edition includes new analytic contributions as well as software survey of analytics and spatial information technology. While the First Edition served the professional community well, the Second Edition has substantially expanded its emphasis for classroom use of the volume. Extensive pedagogic materials have been added, going from the fundamental principles to open-ended exercises, including solutions to selected problems. The text is of value to engineering and business programs that offer courses in Decision and Risk Analysis, Muticriteria Decision-Making, and Facility Location and Layout. It should also be of interest to public policy programs that use geographic Information Systems and satellite imagery to support their analyses.