Multiple Criteria Decision Analysis: Classification Problems and Solutions

Multiple criteria decision analysis (MCDA) techniques are developed to address challenging classification problems arising in engineering management and elsewhere. MCDA consists of a set of principles and tools to assist a decision maker (DM) to solve a decision problem with a finite set of alternatives compared according to two or more criteria, which are usually conflicting. The three types of classification problems to which original research contributions are made are Screening: Reduce a large set of alternatives to a smaller set that most likely contains the best choice. Sorting: Arrange the alternatives into a few groups in preference order, so that the DM can manage them more effectively. Nominal classification: Assign alternatives to nominal groups structured by the DM, so that the number of groups, and the characteristics of each group, seem appropriate to the DM. Research on screening is divided into two parts: the design of a sequential screening procedure that is then applied to water resource planning in the Region of Waterloo, Ontario, Canada; and the development of a case-based distance method for screening that is then demonstrated using a numerical example. Sorting problems are studied extensively under three headings. Case-based distance sorting is carried out with Model I, which is optimized for use with cardinal criteria only, and Model II, which is designed for both cardinal and ordinal criteria; both sorting approaches are applied to a case study in Canadian municipal water usage analysis. Sorting in inventory management is studied using a case-based distance method designed for multiple criteria ABC analysis, and then applied to a case study involving hospital inventory management. Finally sorting is applied to bilateral negotiation using a case-based distance model to assist negotiators that is then demonstrated on a negotiation regarding the supply of bicycle components. A new kind of decision analysis problem, called multiple criteria nominal classification (MCNC), is addressed. Traditional classification methods in MCDA focus on sorting alternatives into groups ordered by preference. MCNC is the classification of alternatives into nominal groups, structured by the DM, who specifies multiple characteristics for each group. The features, definitions and structures of MCNC are presented, emphasizing criterion and alternative flexibility. An analysis procedure is proposed to solve MCNC problems systematically and applied to a water resources planning problem

Factors associated with the decision to investigate child protective services referrals: a systematic review

Background: Limited resources for child protection create challenging decision situations for child protective services (CPS) workers at the point of intake. A body of research has examined the factors associated with worker decisions and processes using a variety of methodological approaches to gain knowledge on decision-making. However, few attempts have been made to systematically review this literature. Objective: As part of a larger project on decision-making at intake, this systematic review addressed the question of the factors associated with worker decisions to investigate alleged maltreatment referrals. Methods: Quantitative studies that examined factors associated with screening decisions in CPS practice settings were included in the review. Database and other search methods were used to identify research published in English over a 35-year period (1980-2015). Findings: Of 1,147 identified sources, 18 studies were selected for full data extraction. The studies were conducted in the U.S., Canada, and Sweden and varied in methodological quality. Most studies examined case factors with few studies examining other domains. Conclusions: To inform CPS policy and practice, additional research is needed to examine the relationships between decision-making factors and case outcomes. Greater attention needs to be given to the organizational and external factors that influence decision-making

Green retrofit of existing non-domestic buildings as a multi criteria decision making process

With increased awareness of natural resources depletion, environmental pollution and social issues, the importance of sustainable development has been emphasised. Sustainable development is accepted as a guiding principle to reconcile economic development with limited natural resources and the dangers of environmental degradation. The building industry is a vital element of any economy and can have a significant impact on the environment. By virtue of the large size of existing buildings, green retrofit of existing buildings is an effective approach to improve building sustainability and energy performance. Unlike domestic building retrofit, bound in the research, non-domestic building retrofit lacks a sufficient research and requires a further investigation. Green retrofit of existing buildings is a complex decision making process. With the rise of sustainability agenda in the building sector, it is essential for decision makers to consider sustainability criteria, which address environmental, economic and social performance. Due to the intrinsic characteristic of existing buildings, technical challenges can emerge when integrating green technologies or measures. The qualitative and quantitative nature of these multiple criteria can increase the complexity of the decision making process. In addition, the decision making process may involve stakeholders from varying backgrounds. The conflicting perspectives can be the main barrier in the decision making of green retrofits. This thesis proposes a framework for green retrofit of existing non-domestic buildings as a multi-criteria decision making process. The framework includes multiple phases: Site and Building Survey, Technology Listing and Screening, and Technology Evaluation with Multi Criteria Decision Making (MCDM) methods. By checking hierarchical information in the Site and Building Survey, basic information can be collected and implications for green technology can be gathered. The Technology Listing and Screening is used to propose potential technologies and further identify the qualified technologies. On top of these phases, technology evaluation with MCDM methods is suggested to conduct in four steps: 1) Criteria development by proposing a multiple criteria tree; 2) Criteria weighting by suggesting the default weights; 3) Technology scoring by presenting a simplified technology scoring approach; 4) Results synthesis. To propose the default weights, a professional survey has been designed to collect the views of experts from different backgrounds in the UK and China. Default weights have been suggested for all the expert group, the architect group, the engineer group, and other expert groups in both countries. The framework has been applied to one UK university building for the retrofit. The main findings are: by using the proposed framework, the possibility of selecting green technologies can be increased; by using the MCDM methods for technology evaluation, the technology ranking can be identified. Scenario analysis and sensitivity analysis have been conducted for technology ranking by applying different sets of default weights. Results show that the changes of criteria weighting for Cost and Payback period can lead to technology ranking changes in all the UK expert scenario. The changes of criteria weighting for all the criteria can lead to a change in technology ranking in the UK architect scenario

CONTRIBUTIONS TO THE THEORY OF SENSITIVITY AND STABILITY ANALYSIS OF MULTI-CRITERIA DECISION MODELS, WITH APPLICATIONS TO MEDICAL DECISION MAKING

Patients are faced with multiple alternatives when selecting the preferred method for colorectal cancer screening, and there are multiple criteria to be considered in the decision process. We model patients’ choices using a multi-criteria decision model, and propose a new approach for characterizing the idiosyncratic preference regions for individuals and for groups of similar patients. We propose an extension of the sensitivity and stability analyses for Analytic Network Models developed by May et al. (2013). We study ANP models to understand how preference regions are created, and how boundaries can be characterized, as the number of criteria increases. For the two-criteria and three-criteria sensitivity and stability analyses, piecewise linear functions and triangular mesh generation, respectively, are used to approximate the boundaries between two adjacent preference regions. We use optimization methods to find the best approximations for the core stability and solution stability regions for cases where two and three criteria are perturbed simultaneously, and there exist an arbitrary number of alternatives. We define sensitivity and stability measures that can be implemented in practice, and that can be considered as a starting point in any medical decision making process. We apply our newly developed methodology to randomly chosen patients, and show how insights derived from the sensitivity and stability of patients’ preferences might be used within the medical decision making process. Individualized stability analysis is informative, but the generalization to groups of similar patients may be even more important for healthcare providers. Our comparisons reveal that a patient’s age may be an effective discriminating factor that should be taken into consideration when extending the individualized sensitivity and stability analysis to groups of patients with similar characteristics

Addressing health literacy in patient decision aids

MethodsWe reviewed literature for evidence relevant to these two aims. When high-quality systematic reviews existed, we summarized their evidence. When reviews were unavailable, we conducted our own systematic reviews.ResultsAim 1: In an existing systematic review of PtDA trials, lower health literacy was associated with lower patient health knowledge (14 of 16 eligible studies). Fourteen studies reported practical design strategies to improve knowledge for lower health literacy patients. In our own systematic review, no studies reported on values clarity per se, but in 2 lower health literacy was related to higher decisional uncertainty and regret. Lower health literacy was associated with less desire for involvement in 3 studies, less question-asking in 2, and less patient-centered communication in 4 studies; its effects on other measures of patient involvement were mixed. Only one study assessed the effects of a health literacy intervention on outcomes; it showed that using video to improve the salience of health states reduced decisional uncertainty. Aim 2: In our review of 97 trials, only 3 PtDAs overtly addressed the needs of lower health literacy users. In 90% of trials, user health literacy and readability of the PtDA were not reported. However, increases in knowledge and informed choice were reported in those studies in which health literacy needs were addressed.ConclusionLower health literacy affects key decision-making outcomes, but few existing PtDAs have addressed the needs of lower health literacy users. The specific effects of PtDAs designed to mitigate the influence of low health literacy are unknown. More attention to the needs of patients with lower health literacy is indicated, to ensure that PtDAs are appropriate for lower as well as higher health literacy patients

Cost-effectiveness of HBV and HCV screening strategies:a systematic review of existing modelling techniques

Introduction: Studies evaluating the cost-effectiveness of screening for Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) are generally heterogeneous in terms of risk groups, settings, screening intervention, outcomes and the economic modelling framework. It is therefore difficult to compare cost-effectiveness results between studies. This systematic review aims to summarise and critically assess existing economic models for HBV and HCV in order to identify the main methodological differences in modelling approaches. Methods: A structured search strategy was developed and a systematic review carried out. A critical assessment of the decision-analytic models was carried out according to the guidelines and framework developed for assessment of decision-analytic models in Health Technology Assessment of health care interventions. Results: The overall approach to analysing the cost-effectiveness of screening strategies was found to be broadly consistent for HBV and HCV. However, modelling parameters and related structure differed between models, producing different results. More recent publications performed better against a performance matrix, evaluating model components and methodology. Conclusion: When assessing screening strategies for HBV and HCV infection, the focus should be on more recent studies, which applied the latest treatment regimes, test methods and had better and more complete data on which to base their models. In addition to parameter selection and associated assumptions, careful consideration of dynamic versus static modelling is recommended. Future research may want to focus on these methodological issues. In addition, the ability to evaluate screening strategies for multiple infectious diseases, (HCV and HIV at the same time) might prove important for decision makers

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Assessment of the added value of the Twente Photoacoustic Mammoscope in breast cancer diagnosis\ud

Purpose: Photoacoustic (PA) imaging is a recently developed breast cancer imaging technique. In order to enhance successful clinical implementation, we quantified the potential clinical value of different scenarios incorporating PA imaging by means of multi-criteria analysis. From this analysis, the most promising area of application for PA imaging in breast cancer diagnosis is determined, and recommendations are provided to optimize the design of PA imaging. - \ud Methods: The added value of PA imaging was assessed in two areas of application in the diagnostic track. These areas include PA imaging as an alternative to x-ray mammography and ultrasonography in early stage diagnosis, and PA imaging as an alternative to Magnetic Resonance Imaging (MRI) in later stage diagnosis. The added value of PA imaging was assessed with respect to four main criteria (costs, diagnostic performance, patient comfort and risks). An expert panel composed of medical, technical and management experts was asked to assess the relative importance of the criteria in comparing the alternative diagnostic devices. The judgments of the experts were quantified based on the validated pairwise comparison technique of the Analytic Hierarchy Process, a technique for multi-criteria analysis. Sensitivity analysis was applied to account for the uncertainty of the outcomes. - \ud Results: Among the considered alternatives, PA imaging is the preferred technique due to its non-invasiveness, low cost and low risks. However, the experts do not expect large differences in diagnostic performance. The outcomes suggest that design changes to improve the diagnostic performance of PA imaging should focus on the quality of the reconstruction algorithm, detector sensitivity, detector bandwidth and the number of wavelengths used. - \ud Conclusion: The AHP method was useful in recommending the most promising area of application in the diagnostic track for which PA imaging can be implemented, this being early diagnosis, as a substitute for the combined use of x-ray mammography and ultrasonography