Thomas L. Saaty

Bio: Thomas L. Saaty is an academic researcher from University of Pittsburgh. The author has contributed to research in topics: Analytic hierarchy process & Analytic network process. The author has an hindex of 92, co-authored 375 publications receiving 95026 citations. Previous affiliations of Thomas L. Saaty include College of Business Administration & Politécnico Grancolombiano.

Prediction, projection and forecasting : applications of the analytic hierarchy process in economics, finance, politics, games and sports

Abstract: We predict when we say in advance, foretell, or prophesy what is likely to happen in the future. We project when we calculate the numerical value associated with a future event. We forecast, a special kind of prediction, on data of past happenings to generate or cast data for future by relying happenings. Generally, one predicts (yes, no) a war, an earthquake or the outcome of a chess match, projects the value of the GNP or of unemployment, and forecasts the weather and, more scientifically, the economic trends. Prediction, projection, and forecasting must be constrained in time and space: when and where. Often the accuracy of a forecast is of interest along with how sensitive the outcome is to changes in the factors involved. Is there a basis for improving the wisdom we need to make correct and useful predictions? We believe there is, and that it can be cultivated by studying the approach given here along with the various examples. To the best of our knowledge, no other work has approached prediction in the scientific framework of hierarchies. Prediction is the synthesis of past and present in an attempt to foretell the future. In our view, creation is not the ultimate phenomenon of the world. Nature creates forms and so do we. The problem is to surmise the eventual purpose, impact, and use of creation. It is the synthesis or outcome of bringing together the results of creation that we need to predict.

Making and validating complex decisions with the ahp/anp

Abstract: Several examples that serve to validate the AHP/ANP with matrices hierarchies and networks are given in this paper. They are then followed by a discussion of the real numbers and how they are generated without the need for an absolute zero, and how they define an absolute scale of measurement that also does not need an absolute zero. In the AHP/ANP the measurement of an alternative depends on what other alternatives it is compared with. The result is that rank can change if alternatives are added or deleted, something that does not occur in one-at-a-time rating of the alternatives by comparing them with an ideal. An example is provided to show that this is natural and need not involve new criteria or change in judgments. A brief discussion of Utility Theory, the other multi-criteria theory, which uses interval scales to measure intangibles and some of its problems and paradoxes, is given. The references at the end include most of the papers that are adverse to the AHP with brief comments about several of them given in the paper.

The allocation of intangible resources: the analytic hierarchy process and linear programming

Abstract: An intangible is an attribute that has no scale of measurement. Intangibles such as effort and skill arise in conjunction with resource allocation but are not usually included directly in a mathematical model because of the absence of a unit of measurement. However, intangibles can be quantified through relative measurement (priorities). Intangible resource allocation uses these priorities along with normalized measures of tangibles (when present) in a linear programming model with coefficients and variables measured in relative terms. The priorities of tangible resources from the optimal solution can then be used to assign monetary values to priorities of any intangible resources.

Absolute and relative measurement with the ahp. the most livable cities in the united states

Abstract: In this paper it is shown that there are two types of measurement involved in the AHP, absolute and relative. The first requires a standard with which to compare elements, but mostly alternatives at the bottom of the hierarchy. The process leads to absolute preservation in the rank of the alternatives no matter how many are introduced. The second is based on paired comparisons among the elements of a set with respect to a common attribute. This process is essential for comparing intangible attributes for which there are no agreed upon measures. At the level of alternatives new elements (i.e. alternatives) do introduce new information generated by the changing number in the set and by their measurement which essentially rescales the criteria and hence can lead to reversals of previous rank orders. Absolute measurement is used on standardized problems whereas relative measurement is used in new learning situations. Absolute measurement is applied to the Rand McNally study that ranks cities according to livability in the United States.

The Analytic Hierarchy Process

Abstract: This chapter provides an overview of Analytic Hierarchy Process (AHP), which is a systematic procedure for representing the elements of any problem hierarchically. It organizes the basic rationality by breaking down a problem into its smaller constituent parts and then guides decision makers through a series of pair-wise comparison judgments to express the relative strength or intensity of impact of the elements in the hierarchy. These judgments are then translated to numbers. The AHP includes procedures and principles used to synthesize the many judgments to derive priorities among criteria and subsequently for alternative solutions. It is useful to note that the numbers thus obtained are ratio scale estimates and correspond to so-called hard numbers. Problem solving is a process of setting priorities in steps. One step decides on the most important elements of a problem, another on how best to repair, replace, test, and evaluate the elements, and another on how to implement the solution and measure performance.

Fuzzy Set Theory - and Its Applications

Abstract: Fuzzy Set Theory - And Its Applications, Third Edition is a textbook for courses in fuzzy set theory. It can also be used as an introduction to the subject. The character of a textbook is balanced with the dynamic nature of the research in the field by including many useful references to develop a deeper understanding among interested readers. The book updates the research agenda (which has witnessed profound and startling advances since its inception some 30 years ago) with chapters on possibility theory, fuzzy logic and approximate reasoning, expert systems, fuzzy control, fuzzy data analysis, decision making and fuzzy set models in operations research. All chapters have been updated. Exercises are included.

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or