Multi-attribute Decision Theory Research Articles

Proposal and application of a Sustainable Development Index

This work shows the methodology used to design a Sustainable Development Index (SDI), and its application to a region within the Coatzacoalcos river basin. This region is one of the more highly industrialized zones in Mexico, and is located in the State of Veracruz, about 800 km southeast of Mexico City. The SDI was formed within the framework of the driving forces, state, and response (DSR) philosophy. Within this framework we have included an indicator about environmental accounting in order to determine the monetary value of losses due to depletion and deterioration of natural resources. At the same time we use the Multi-Attribute Decision Theory methodology along with 21 indicators; most of them were designed and calculated specifically for this work. The indicators represent the environmental, economic, and social characteristics of the region. The utility functions that were designed for grading the region in each attribute used international and national parameters of performance. The SDI was applied to seven municipalities. The Figure of Merit obtained by each municipality served to rank them in terms of their closeness to a Sustainable Development. The results of the analysis also identified and prioritized the most urgent problems that need to be solved in order to obtain an improvement in the development of the municipalities in accordance to sustainability and resource management criteria.

Development of a methodology for evaluating air pollution options for improving the air quality in Mexico City

This paper describes a methodology for evaluating air pollution control strategies for Mexico City. The method-ology combines Mixed Integer Linear Programming (MILP) and Multi-Attribute Decision Theory (MADT) to design, evaluate and rank groups of options (single actions) to combat air pollution, considering economic, technical, environmental, social, political and institutional factors. Groups of options or strategies are formed using MILP. These strategies are then evaluated and ranked utilizing MADT. As an example of the capabilities of this methodology, this paper presents the procedure to design strategies and the evaluation and ranking of three of these strategies. This methodology was designed to help authorities in the decision-making process for air pollution control, and was developed specifically for the Mexico City case, although the experience gained in this work can be used to develop similar methodologies for other metropolitan areas throughout the world.

Multiattribute Assessment of Alternative Cropping Systems

AbstractMultiattribute rankings of seventy‐two alternative midwestern cropping systems involving corn, soybeans, and alfalfa hay are analyzed from profitability and environmental quality perspectives. Environmental consequences are simulated using EPIC and GLEAMS, and profitability is based on budget analysis. Results are analyzed using an algorithm based on multiattribute decision theory. A corn‐soybean rotation using low input levels and minimum tillage on high‐productivity soil, and continuous corn using low input levels and minimum tillage on low‐productivity soil are in the preferred set regardless of whether profits or preserving the environment is the first priority for the decision maker.

Ranking radiotherapy treatment plans using decision-analytic and heuristic techniques

Radiotherapy treatment optimization is done by generating a set of tentative treatment plans, evaluating them, and selecting the plan closest to achieving a set of conflicting treatment objectives. The evaluation of potential plans involves making trade-offs among competing possible outcomes. Multiattribute decision theory provides a framework for specifying such trade-offs and using them to select optimal actions. Using these concepts, we have developed a plan-ranking model which ranks a set of tentative treatment plans from best to worst. Heuristics are used to refine this model so that it reflects the clinical condition of the patient being treated and the practice preferences of the physician prescribing the treatment. A figure of merit is computed for each tentative plan and is used to rank the plans. The approach described is very general and can be used for other medical domains having similar characteristics. The figure of merit can also be used as an objective function by computer programs that attempt to automatically generate an optimal treatment plan.

The analytic hierarchy process as a model base for a merit salary recommendation system

This paper describes how the Analytic Hierarchy Process (AHP), as developed by T.L. Saaty and others, can be used in a merit salary increase Decision Support System (DSS). The basic rationale for the system is that merit increases should be proportional to, or at least be correlated with, the relative value of contribution during the period for which the reward is relevant. Details of AHP are provided as needed for the benefit of the reader not familiar with this widely used tool of multi-attribute decision theory. The proposed merit salary recommendation system is explained, and illustrated using hypothetical data.

Evaluating Competing R&D Investments

Since R&D projects typically last for a number of years, their quantitative analysis and comparison requires some rational means of adjusting project worth as a function of the time profile of project expenditures and returns. An additional adjustment must be made to account for the risk that is present in virtually all R&D activities. Since many projects last for as long as 10 years, these time and risk adjustments may be quite substantial, and may dominate the decision calculus. This paper examines the state of the art in such decision-making models, and recommends methods for improvement. We deal first with adjustments for time alone, ignoring risk. Later, we examine methods for adjusting for both time and risk. Adjusting for Time Alone The most common method of adjusting for time profiles of returns on capital investment projects is the present value technique (here we subsume both net present value and internal rate of return under the same heading). A 1978 survey suggested that more than 85 percent of firms use such techniques to make capital budgeting decisions (1). In another study, Rizzuto and Cook show that rate of return is the primary determinant in management choices abo'ut R&D spending levels However, a third, experimental, study shows that the manager's discounted cash flow is not always consistent with the classical present value approach (3). While present value techniques are sound and well-seasoned methods, they do require several restrictive assumptions about the decision maker's time preferences. These assumptions, which are usually unexamined, limit the applicability of the technique. The choice among cash flows with different time profiles is a multi-attribute decision theory problem of a special type. In choices of cash flows over time, the decision maker would like to maximize the cash flow in each year. Since it is rare that any choice will yield this utopian solution, the practicing manager must trade off one year's cash flow against another's. A decision theorist would model this tradeoff process with a multi-attribute value function. This may be very difficult in practice. Decision theory, however, allows us to describe the behavioral properties implied by different tradeoff techniques. The present value technique is a well-known and trusted method for accomplishing tradeoffs among cash flows. The decision maker who uses this technique, however, is assumed to possess the following preference characteristics: 1. Suppose the decision maker is to choose between two cash flow streams, x = (x1, x2, . . ., xn), and y = (y1, y2, . . ., yn). It is assumed that the present-value decision maker will prefer cash flow stream x to y if one year's cash flow in x exceeds the same year's flow in y while all the other years are equal. This assumption, called dominance, seems natural for virtually any rational decision maker. 2. Suppose that the decision maker is faced with two specific cash flow streams, x = (10,16,20,25,50,100), and y = (10,15,20,40,50,100). Notice that these two streams differ only in Years 2 and 4. Now further suppose that the decision maker preferred x to y due to the slightly higher return in Year 2 which would help in some temporary cash flow problem. If the decision maker is to satisfy the assumptions of present value, then the choice between x and y must not change if any of the cash flows (other than Years 2 and 4) are changed by an equal amount in both x and y. So assume that x = (100,16,20,25,50,100), and y = (100,15,20,30,50,100). With such high returns in Year 1, the short term cash flow problem in Year 2 is no longer a matter for concern, so the decision maker decides to choose y. This change in preferences is inconsistent with the assumptions about the present-value decision maker. 3. It is assumed that the present-value decision maker is indifferent between one dollar of cash flow in year t and 1 + r dollars in year t + 1, where r is the relevant discount rate. …

Multiattribute Decision Theory and Forest Management: A Discussion and Application

Abstract The procedures required to implement Multiattribute Decision Theory (MDT) are presented. MDT is then applied to the management of a stand of timber owned by a nonindustrial private forest (NIPF) landowner who wanted to maximize both timber income and esthetic benefits. Harvesting/regeneration procedures of intermediate intensity maximize the well-being of a segment of NIPF landowners. For. Sci. 33(4):835-845.

Concepts, Theory, and Techniques PRINCIPLES OF MULTIOBJECTIVE OPTIMIZATION*

ABSTRACTThis paper attempts to isolate and analyze the principal ideas of multiobjective optimization. We do this without casting aspersions on single‐objective optimization or championing any one multiobjective technique. We examine each fundamental idea for strengths and weaknesses and subject two—efficiency and utility—to extended consideration. Some general recommendations are made in light of this analysis. Besides the simple advice to retain single‐objective optimization as a possible approach, we suggest that three broad classes of multiobjective techniques are very promising in terms of reliably, and believably, achieving a most preferred solution. These are: (1) partial generation of the efficient set, a rubric we use to unify a wide spectrum of both interactive and analytic methods; (2) explicit utility maximization, a much‐overlooked approach combining multiattribute decision theory and mathematical programming; and (3) interactive implicit utility maximization, the popular class of methods introduced by Geoffrion, Dyer, and Feinberg [24] and extended significantly by others.

Application of Value-lmpact Methodology in the Design Analysis of a Nuclear Safety System

The application of a value-impact methodology to a nuclear safety system design analysis has been investigated. The theoretical framework of multi-attribute decision theory and cost-benefit analysis is combined with reliability, availability, and probabilistic risk assessment techniques to analyze three design alternatives for the auxiliary feedwater system of a pressurized water reactor. Selected attributes pertaining to financial impact, investment risk, health risk, and licensability are used to rank the alternatives. External factors--such as the effect on the schedule of other plants, impact on property value, and emotional effects on population--that are potentially large were not considered. Standard reference tables were developed as a user's guide for value-impact calculations.

Risk Assessment of Alternative Proliferation Routes

Multi-Attribute Decision Theory is applied to rank 11 alternative routes to nuclear proliferation in order of difficulty in acquiring nuclear weapons by nonnuclear countries. The method is based on reducing the various variables affecting the decision to a single function providing a measure for the proliferation route. The results indicate that the most difficult route to obtain atomic weapons is through nuclear power reactors, specifically the liquid-metal fast breeder reactor, heavy water Canada deuterium uranium reactor, and light water reactors such as boiling water and pressurized water reactors. The easiest routes are supercritical centrifuge isotope separation, laser isotope separation, and research reactor. However, nonnuclear routes available that result in substantial damage to life and property are easier than any nuclear route.

What can the regression model of human judgment learn from multi-attribute decision theory?

Zeleny's recent conjecture that multi-attribute decision theory may help to overcome the inadequacies of the linear regression model is incorrect. Recognition of the information processing advantages inherent in multiple -attribute decision situations combined with a requirement of transitivity itself implies linear objective functions. This follows from some recent developments by a psychologist and an economist in the analysis of individual and collective decision processes, developments which do not take as their starting point the paradigm of choice offered in utility theory.