Showing papers on "Analytic hierarchy process published in 1990"

Remarks on the analytic hierarchy process

Abstract: The analytic hierarchy process AHP is flawed as a procedure for ranking alternatives in that the rankings produced by this procedure are arbitrary. This paper provides a brief review of several areas of operational difficulty with the AHP, and then focuses on the arbitrary rankings that occur when the principle of hierarchic composition is assumed. This principle requires that the weights on the higher levels of a hierarchy can be determined independently of the weights on the lower levels. Virtually all of the published examples of the use of the AHP to evaluate alternatives relative to a set of criteria have assumed this principle. The key to correcting this flaw is the synthesis of the AHP with the concepts of multiattribute utility theory.

An exposition of the AHP in reply to the paper “remarks on the analytic hierarchy process”

Abstract: It is a fact that people make decisions and have been making decisions for a very long time. Contrary to what some of us who are interested in decision-making may like to believe, most people do not take seriously the existence of theories which purport to set their thinking and feeling right. They claim to know their own value system and what they want. They may wonder how anyone else can know well enough to tell them how best to organize their thinking in order to make better choices. Yet, research has shown that complex decisions are beyond the capacity of the brain to synthesize intuitively and efficiently. Since decision making is a natural characteristic of people, how do we describe what they do so that an ordinary mortal can understand what we are saying? We do not wish to legislate the method with which people should make decisions, but only to describe it even when it is prescribed by some method. In the process, we may learn things that can help people make better decisions. How? The Analytic Hierarchy Process (AHP) (Forman et al., Harker 1986, Harker and Vargas 1987, Saaty 1986, 1988a, b, Saaty and Vargas 1987, Xu 1988, Golden et al. 1989, Saaty and Alexander 1989) is a theory of measurement. When applied in decision making it assists one to describe the general decision operation by decomposing a complex problem into a multi-level hierarchic structure of objectives, criteria, subcriteria and alternatives. The AHP provides a fundamental scale of relative magnitudes expressed in dominance units to represent judgments in the form of paired comparisons. A ratio scale of relative magnitudes expressed in priority units is then derived from each set of comparisons. An overall rcatio scale of priorities is then synthesized to obtain a ranking of the alternatives. From its axioms to its procedures, the AHP has turned out to be historically and theoretically a different and independent theory of decision making from utility theory. Much as a dialogue evolved in mathematics around the consistency of different geometries and around absolute and relative space and time in physics, both to dispel absolute notions, those who believe that only utility theory can tell us the absolute truth about man's decision-making might take a close look at the AHP. It has found varied and serious applications. It also has a particular way of generating ratio scales and dealing with inconsistency in judgment that have contributed to its effectiveness in resource allocation and in the setting of priorities by a group of decision makers. Utility theory is a normative process. The AHP as a descriptive theory encompasses procedures leading to outcomes as would be ranked by a normative theory. But it must go beyond to deal with outcomes not accounted for by the demanding assumptions of a normative theory. We must briefly describe the AHP to enable the reader to see that a practicable theory based on ratio scales need not dilute itself to satisfy expectations of people who derive their understanding from a theory based on interval scales. This is particularly true if the rival theory, in aspiring for generality, also makes unrealistic assumptions, for example about the transitivity and consistency of preferences and the difficult use of lotteries,

Multi Criteria Decision Making and the Analytic Hierarchy Process

Abstract: The Analytic Hierarchy Process (Saaty, 1977 and 1980) is a multiple criterion evaluation methodology that is both descriptive and prescriptive. The Analytic Hierarchy Process (AHP) is, in many ways, similar to Multi Attribute Utility Theory. However, unlike MAUT, AHP does not prescribe that judgments be perfectly consistent, nor does it prescribe when or when not to allow for rank reversals. AHP allows the decision makers to decide how much inconsistency is reasonable, if any, and whether nor not rank reversal (a reflection of relative rather absolute worth) should be permitted.

Application of Analytical Hierarchy Process in Operations Management

Abstract: The use of Analytical Hierarchy Process (AHP) is an effective way to deal with qualitative decision areas of operations management. Four published applications of AHP are briefly reviewed in forecasting, supplier selection, facility location, and choice of technology. Furthermore, four more potential applications are suggested in other areas of operations management, including product design, plant layout, maintenance frequency selection, and choice of logistic carrier. In addition, suggestions for other areas of research are discussed.

Some Comments on the Analytic Hierarchy Process

Abstract: Some comments are made on the analytic hierarchy process of Thomas L. Saaty, which has gained widespread acceptance as a valuable tool for multicriteria decision-making. Saaty's validation of the method against physical laws is criticized, a multiplicative scale is suggested for making judgements, and the problem of rank reversal is discussed with reference to two published papers.

The analytic hierarchy process in conflict management

Abstract: The Analytic Hierarchy Process (AHP) is a theory of measurement. When applied in decision‐making, it assists one to describe the general decision operation by decomposing a complex problem into a multi‐level hierarchic structure of objectives, criteria, subcriteria and alternatives. The AHP provides a fundamental scale of absolute magnitudes to represent judgments in the form of paired comparisons. A ratio scale of relative magnitudes expressed in priority units is then derived from each set of comparisons. An overall ratio scale of priorities is synthesized to obtain ranking of the alternatives. What is illustrated here is an application of the AHP to a retributive ongoing conflict in which the parties maximize both their benefits from and costs to the opponent. Using the AHP, benefit and cost hierarchies are constructed for the parties, four for each, involving actual and perceived benefits and costs of concessions. Similarly, a mediator must construct his own hierarchies to evaluate and propose changes in judgments and new concessions to improve an impasse in negotiation.

The Analytic Hierarchy Process and its Application to an Information Technology Decision

Abstract: This paper describes how the analytic hierarchy process was applied to a decision concerning the selection of a computer operating system. Various practical issues and problems which arose whilst using the process are discussed. The method was found to be a useful aid for identifying the criteria upon which a decision depends. It also revealed useful data about the concerns and preferences of decision-makers. Some problems were, however, encountered when assessing the importance of an intangible factor relative to a tangible factor. Also, it was difficult to interpret the options' final scores because the method does not provide an indication of statistical significance.

Combining qualitative and quantitative factors—an analytic hierarchy approach

Abstract: The Analytic Hierarchy Process (AHP) provides a general theory of measurement for expressing both tangible and intangible factors. In this paper, intangible or qualitative factors are looked upon as dimensions which we have not yet learned how to measure very well. Through a redundant paired-comparison process. AHP allows us to translate qualitative preferences into ratio scaled data. In addition, the structuring stage of AHP facilitates problem understanding.

Bids Considering Multiple Criteria

Abstract: Typically, the only criterion quantitatively considered in competitive bidding optimization is profit criterion. This may or may not lead to suboptimal decisions when a decision maker's total utility is considered, depending upon the importance of profit relative to other criteria, such as loss avoidance or work force continuity. Common sense generally provides a basis for subjective modification of profit‐based bidding strategies in order to incorporate additional criteria. However, the more complex the situation, the more difficult it becomes to determine what strategy modifications are appropriate. This paper presents a quantitative method for incorporating decision‐maker preferences into the bidding process when multiple criteria are to be considered. The method is based upon the merging of stochastic bidding models with the analytical hierarchy process (AHP). Inputs are cost data, competitor data, and decision‐maker preferences, while output is a set of composite weights by which alternative bid mark...

Judgmental adjustment of earnings forecasts

Abstract: Earnings forecasts have received a great deal of attention, much of which has centered on the comparative accuracy of judgmental and objective forecasting methods. Recently, studies have focused on the use of combinations of subjective and objective forecasts to improve forecast accuracy. This research offers an extension on this theme by subjectively modifying an objective forecast. Specifically, ARIMA forecasts are judgmentally adjusted by analysts using a structured approach based on Saaty's (1980) analytic hierarchy process. The results show that the accuracy of the unadjusted objective forecasts can be improved when judgmentally adjusted.

A tradeoff analysis for rough terrain cargo handlers using the AHP: an example of group decision making

Abstract: The results of a case study designed to select the next generation of rough-terrain cargo handlers for the US Army are presented. Three alternatives were identified and ultimately ranked using the analytic hierarchy process (AHP). This framework permits decision makers to conduct tradeoffs among incommensurate criteria without having to rely on a single measure. The evaluation team consisted of five program managers and engineers. Special attention is paid to the efforts at data collection and the accompanying group dynamics. The objective hierarchy contained 12 attributes. In general, the AHP was found to be quite accessible and conducive to concensus building. Once the attributes were defined, the decision makers had little difficulty in furnishing the necessary data and discussing the intermediate results. >

A comparative study of multiattribute decision making methodologies

Abstract: Three “real life” cases are considered in this paper to apply and compare the rankings obtained by the Analytic Hierarchy Process (AHP) and other Multicriteria Decision Making (MCDM) techniques such as Simple Additive Weighting (SAW), ELECTRE and Weighted Linear Assignment Method (WLAM). The results indicated that the AHP, SAW, and ELECTRE rankings do not differ significantly, however, the WLAM tends to exhibit more disagreement. However, because of the limited nature of this study, we do not suggest this as a general conclusion.

Use of a Simple Multi-Attribute Value Function Incorporating Visual Interactive Sensitivity Analysis for Multiple Criteria Decision Making

Abstract: V·I·S·A is a computer program for multiple criteria decision aid, based on a simple weighted multi-attribute value function, incorporating a hierarchical structure of criteria and visual interactive sensitivity analysis. The use of a model of this kind as an aid to multi-attribute decision making is nothing new. Long before MCDM became an established field of study in the 1970’s use of models of this kind been reported in the literature, for example, Churchman and Ackoff, 1954. Many popular approaches to decision aiding adopt the same framework, for example, Edwards’ SMART (Edwards, 1982), the Analytic Hierarchy Process developed by Saaty (Saaty, 1980), Social Cost Benefit Analysis (Lichfield et al., 1975). The approach is best suited to the problem of choosing a preferred alternative from a set of well defined alternatives, or to indicate a preference ordering over such a set of alternatives. There are many other approaches suited to this type of problem, for example, the Electre methods and Promethee. However, few approaches have been developed to handle a situation in which the decision maker wants to take account of very many criteria; in such a situation those methods incorporating a hierarchical structure of criteria are most appropriate, namely the multi-attribute value function and the Analytic Hierarchy Process.

Hierarchical sensitivity analysis of priority used in analytic hierarchy process

Abstract: The analytic hierarchy process (AHP) initialed by Saaty (1980) has recently been attracting attention as a useful support method for multi-objective decision making. This paper presents some useful theorems for the sensitivity analysis of priority that is playing an important role in the AHP. These theorems are derived from the principle of hierarchical composition which is expressed in the form of a reachability matrix. Using the theorems, we can easily calculate the degrees of effects caused by local or global changes in the priorities of some criteria, and also we can examine the possibility of rank reversal among alternatives. Furthermore, by applying these theorems to a dwelling selection problem, this paper verifies their effectiveness.

Multiple Criteria Decision Aid: An Overview

Abstract: What do we mean by “Multiple Criteria Decision Aid (MCDA)”? To answer this question is far from being an easy task. Some papers in this book contain important elements of response.

On a Consensus Measure in a Group MCDM Problem

Abstract: A method for consensus measuring in a group decision problem is presented for the multiple criteria case. The decision process is supposed to be carried out according to Saaty’s Analytic Hierarchy Process, and hence using pairwise comparison among the alternatives. Using a suitable distance between the experts’ judgements, a scale transformation is proposed which allows a fuzzy interpretation of the problem and the definition of a consensus measure by means of fuzzy tools as linguistic quantifiers. Sufficient conditions on the expert’s judgements are finally presented, which guarantee any a priori fixed consensus level to be reached.

Some problems in using benefit'cost ratios with the analytic hierarchy process

Abstract: For Analytic Hierarchy Process applications having separate benefit and cost output vectors, Saaty has recommended choosing a solution using a simple benefit/cost ratio procedure. But, even when benefits and costs are known with certainty and measured in dollars, it is shown that this procedure does not, in general, yield an optimal solution. An incremental analysis, with further specification of an appropriate cutoff rate, is shown to be required. Saaty's procedure is also shown to be sensitive to arbitrary semantic changes in benefit and cost labelling, while proper procedures, such as the one proposed herein, do not have that sensitivity.