Analyzing evacuation decisions using multi-attribute utility theory (MAUT)

Emergency managers are faced with critical evacuation decisions. These decisions must balance conflicting objectives as well as high levels of uncertainty. Multi-Attribute Utility Theory (MAUT) provides a framework through which objective trade-offs can be analyzed to make optimal evacuation decisions. This paper is the result of data gathered during the European Commission Project, Evacuation Responsiveness by Government Organizations (ERGO) and outlines a preliminary decision model for the evacuation decision. The illustrative model identifies levels of risk at which point evacuation actions should be taken by emergency managers in a storm surge scenario with forecasts at 12 and 9 hour intervals. The results illustrate how differences in forecast precision affect the optimal evacuation decision. Additional uses for this decision model are also discussed along with improvements to the model through future ERGO data-gathering.

Modelos quantitativos de apoio as decisões: II

O sucesso da aplicação de técnicas de Análise das Decisões como apoio em problemas com um único objetivo predominante abriu caminho para estudos de problemas mais ambiciosos como os de decisões com multicritérios e decisões e de grupo (estes dois tipos utilizam metodologias muito semelhantes). Como evolução natural da Análise das Decisões, resultou a metodologia MAUT (Multi-Attribute Utility Theory). Seu rigorismo teórico torna as aplicações difíceis para um analista menos preparado. Como conseqüência, surgiu a metodologia AHP (Analytic Hierarchy Process) de utilização extremamente simples. A crítica ao AHP veio da escola européia que criou uma série de métodos conhecidos pela abreviação comum: MCDA (Multicriteria Decision Aid).

New directions in Stochastic Multicriteria Acceptability Analysis

Decisions taken in modern organizations are often multi-dimensional, involving multiple decision makers and several criteria measured on different scales. Multiple Criteria Decision Making (MCDM) methods are designed to analyze and to give recommendations in this kind of situations. Among the numerous MCDM methods, two large families of methods are the multi-attribute utility theory based methods and the outranking methods. Traditionally both method families require exact values for technical parameters and criteria measurements, as well as for preferences expressed as weights. Often it is hard, if not impossible, to obtain exact values. Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of methods designed to help in this type of situations where exact values are not available. Different variants of SMAA allow handling all types of MCDM problems. They support defining the model through uncertain, imprecise, or completely missing values. The methods are based on simulation that is applied to obtain descriptive indices characterizing the problem. In this thesis we present new advances in the SMAA methodology. We present and analyze algorithms for the SMAA-2 method and its extension to handle ordinal preferences. We then present an application of SMAA-2 to an area where MCDM models have not been applied before: planning elevator groups for high-rise buildings. Following this, we introduce two new methods to the family: SMAA-TRI that extends ELECTRE TRI for sorting problems with uncertain parameter values, and SMAA-III that extends ELECTRE III in a similar way. An efficient software implementing these two methods has been developed in conjunction with this work, and is briefly presented in this thesis. The thesis is closed with a comprehensive survey of SMAA methodology including a definition of a unified framework.

Leilões eletrônicos reversos multiatributo : uma abordagem de decisão multicritério como instrumento de agregação de valor aos processos de compras do setor público brasileiro

Leilões são instituições seculares utilizadas nas relações comerciais entre indivíduos e organizações. Provêem maior flexibilidade aos processos de determinação de preços e alocação de bens, aumentando o espaço para negociações entre compradores e vendedores. Na Internet, têm sido empregados, de maneira crescente, em atividades de comércio eletrônico B2B e G2B, em sua maioria, através da modalidade de leilão reverso. No entanto, seu aspecto unidimensional reduz as negociações à variável preço, produzindo, muitas vezes, resultados aquém do desejado. No caso brasileiro, o Governo Federal instituiu o Portal Comprasnet, através do qual, as organizações públicas adquirem bens e serviços de fornecedores cadastrados. Dentre as modalidades de licitação disponíveis, destaca-se o Pregão Eletrônico, um mecanismo de leilão eletrônico reverso baseado no atributo preço, através do qual, fornecedores submetem lances decrescentes, na disputa por contratos do setor público. No presente trabalho, o autor propõe uma abordagem de decisão multicritério, baseada na Teoria da Utilidade Multiatributo, como uma alternativa para a adoção de leilões reversos baseados em múltiplos atributos e, consequentemente, para uma maior agregação de valor pelas organizações compradoras do setor público brasileiro.

MoSAC: um módulo para seleção de configurações arquiteturais baseado em critérios de QoS no contexto de sistema distribuídos autoadaptativos

The process for choosing the best components to build systems has become increasingly complex. It becomes more critical if it was need to consider many combinations of components in the context of an architectural configuration. These circumstances occur, mainly, when we have to deal with systems involving critical requirements, such as the timing constraints in distributed multimedia systems, the network bandwidth in mobile applications or even the reliability in real-time systems. This work proposes a process of dynamic selection of architectural configurations based on non-functional requirements criteria of the system, which can be used during a dynamic adaptation. This proposal uses the MAUT theory (Multi-Attribute Utility Theory) for decision making from a finite set of possibilities, which involve multiple criteria to be analyzed. Additionally, it was proposed a metamodel which can be used to describe the application s requirements in terms of the non-functional requirements criteria and their expected values, to express them in order to make the selection of the desired configuration. As a proof of concept, it was implemented a module that performs the dynamic choice of configurations, the MoSAC. This module was implemented using a component-based development approach (CBD), performing a selection of architectural configurations based on the proposed selection process involving multiple criteria. This work also presents a case study where an application was developed in the context of Digital TV to evaluate the time spent on the module to return a valid configuration to be used in a middleware with autoadaptative features, the middleware AdaptTV

Dominance Measuring Method Performance under Incomplete Information about Weights.

In multi-attribute utility theory, it is often not easy to elicit precise values for the scaling weights representing the relative importance of criteria. A very widespread approach is to gather incomplete information. A recent approach for dealing with such situations is to use information about each alternative?s intensity of dominance, known as dominance measuring methods. Different dominancemeasuring methods have been proposed, and simulation studies have been carried out to compare these methods with each other and with other approaches but only when ordinal information about weights is available. In this paper, we useMonte Carlo simulation techniques to analyse the performance of and adapt such methods to deal with weight intervals, weights fitting independent normal probability distributions orweights represented by fuzzy numbers.Moreover, dominance measuringmethod performance is also compared with a widely used methodology dealing with incomplete information on weights, the stochastic multicriteria acceptability analysis (SMAA). SMAA is based on exploring the weight space to describe the evaluations that would make each alternative the preferred one.

Dominance intensity measure within fuzzy weight oriented MAUT: an application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers’ preferences, and imprecise weights are represented by trapezoidal fuzzy weights.The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights. An example concerning the selection of intervention strategies to restore an aquatic ecosystem contaminated by radionuclides illustrates the approach. Monte Carlo simulation techniques have been used to show that the proposed method performs well for different imprecision levels in terms of a hit ratio and a rank-order correlation measure.

Veto values in Group Decision Making within MAUT: aggregating complete rankings derived from dominance intensity measures

We consider a groupdecision-making problem within multi-attribute utility theory, in which the relative importance of decisionmakers (DMs) is known and their preferences are represented by means of an additive function. We allow DMs to provide veto values for the attribute under consideration and build veto and adjust functions that are incorporated into the additive model. Veto functions check whether alternative performances are within the respective veto intervals, making the overall utility of the alternative equal to 0, where as adjust functions reduce the utilty of the alternative performance to match the preferences of other DMs. Dominance measuring methods are used to account for imprecise information in the decision-making scenario and to derive a ranking of alternatives for each DM. Specifically, ordinal information about the relative importance of criteria is provided by each DM. Finally, an extension of Kemeny's method is used to aggregate the alternative rankings from the DMs accounting for the irrelative importance.

A decision support framework for infrastructure maintenance investment decision-making

Infrastructure management agencies are facing multiple challenges, including aging infrastructure, reduction in capacity of existing infrastructure, and availability of limited funds. Therefore, decision makers are required to think innovatively and develop inventive ways of using available funds. Maintenance investment decisions are generally made based on physical condition only. It is important to understand that spending money on public infrastructure is synonymous with spending money on people themselves. This also requires consideration of decision parameters, in addition to physical condition, such as strategic importance, socioeconomic contribution and infrastructure utilization. Consideration of multiple decision parameters for infrastructure maintenance investments can be beneficial in case of limited funding. Given this motivation, this dissertation presents a prototype decision support framework to evaluate trade-off, among competing infrastructures, that are candidates for infrastructure maintenance, repair and rehabilitation investments. Decision parameters' performances measured through various factors are combined to determine the integrated state of an infrastructure using Multi-Attribute Utility Theory (MAUT). The integrated state, cost and benefit estimates of probable maintenance actions are utilized alongside expert opinion to develop transition probability and reward matrices for each probable maintenance action for a particular candidate infrastructure. These matrices are then used as an input to the Markov Decision Process (MDP) for the finite-stage dynamic programming model to perform project (candidate)-level analysis to determine optimized maintenance strategies based on reward maximization. The outcomes of project (candidate)-level analysis are then utilized to perform network-level analysis taking the portfolio management approach to determine a suitable portfolio under budgetary constraints. The major decision support outcomes of the prototype framework include performance trend curves, decision logic maps, and a network-level maintenance investment plan for the upcoming years. The framework has been implemented with a set of bridges considered as a network with the assistance of the Pima County DOT, AZ. It is expected that the concept of this prototype framework can help infrastructure management agencies better manage their available funds for maintenance.

Värdering av kriterier vid stora investeringar : En jämförelse mellan olika intressenters uppskattningar av kriterier

In what way does different stakeholders assess a decision and its consequences, and how do these assessments differ? When a company stands before a big decision, they need to consider aspects that are economic, ecologic and social. To make a good decision they need to consider the society and its different stakeholder groups. This study examined how different groups values and weights different criteria. The study has been done with the project Sundsvall logistics park as a case, with criteria related to that project. The goal of the study was to find a way to value and weight different criteria and then compare how the company and the stakeholders assesses these criteria. This has been done through interviews with relevant people that has got extra knowledge about the project Sundsvall logistics park, and through a survey that has been sent out to residents of Sundsvall. The informants and respondents got to assess values and weights to the criteria relative to an indirect alternative where the logistics park isn’t built. The data was then compiled using multi attribute utility theory as a tool to present the comparison. The result of the study suggests that the differences between the valuations and weightings of the criteria is partly due to an uncertainty in how the logistics park would affect the criteria, but that the biggest reason probably depends on what perspective the person is viewing the logistics park from. If the person is viewing the logistics park from an industrial perspective, the criteria related to industrial development is getting more important and is going to take up more room in the analysis. If the person is viewing the logistics park from an individual and social perspective, the criteria related to that is more important and takes up more room in the analysis.

Simple models for multi-attribute choice with many alternatives: When it does and does not pay to face tradeoffs with binary attributes

Working Paper no longer available. Please contact the author.

Visual attention and attribute attendance in multi-attribute choice experiments

Decision strategies in multi-attribute Choice Experiments are investigated using eye-tracking. The visual attention towards, and attendance of, attributes is examined. Stated attendance is found to diverge substantively from visual attendance of attributes. However, stated and visual attendance are shown to be informative, non-overlapping sources of information about respondent utility functions when incorporated into model estimation. Eye-tracking also reveals systematic nonattendance of attributes only by a minority of respondents. Most respondents visually attend most attributes most of the time. We find no compelling evidence that the level of attention is related to respondent certainty, or that higher or lower value attributes receive more or less attention

Production under uncertainty and choice under uncertainty in the emergence of generalized expected utility theory

This paper presents a personal view of the interaction between the analysis of choice under uncertainty and the analysis of production under uncertainty. Interest in the foundations of the theory of choice under uncertainty was stimulated by applications of expected utility theory such as the Sandmo model of production under uncertainty. This interest led to the development of generalized models including rank-dependent expected utility theory. In turn, the development of generalized expected utility models raised the question of whether such models could be used in the analysis of applied problems such as those involving production under uncertainty. Finally, the revival of the state-contingent approach led to the recognition of a fundamental duality between choice problems and production problems.

Background risk in generalized expected utility theory

In this paper, it is shown that, for a wide range of risk-averse generalized expected utility preferences, independent risks are complementary, contrary to the results for expected utility preferences satisfying conditions such as proper and standard risk aversion.

Multi-attribute classification of housing conservation status in urban regeneration actions

Urban regeneration is more and more a “universal issue” and a crucial factor in the new trends of urban planning. It is no longer only an area of study and research; it became part of new urban and housing policies. Urban regeneration involves complex decisions as a consequence of the multiple dimensions of the problems that include special technical requirements, safety concerns, socio-economic, environmental, aesthetic, and political impacts, among others. This multi-dimensional nature of urban regeneration projects and their large capital investments justify the development and use of state-of-the-art decision support methodologies to assist decision makers. This research focuses on the development of a multi-attribute approach for the evaluation of building conservation status in urban regeneration projects, thus supporting decision makers in their analysis of the problem and in the definition of strategies and priorities of intervention. The methods presented can be embedded into a Geographical Information System for visualization of results. A real-world case study was used to test the methodology, whose results are also presented.