Multiattribute Utility Analysis Research Articles

Application of Multi-Attribute Utility Analysis as a Methodological Framework in Academic–Clinical Partnership Evaluation

A method called multi-attribute utility analysis (MAUA) provides a decision-making framework that facilitates comparative analysis of multiple real-world decision alternatives with unique complex attributes. Utility analysis as a measure of effectiveness has been minimally used by educational researchers to date, despite clear relevance in complex decision-making. To illustrate its viability, the application of MAUA was modeled for two example academic programs with diverse partnership priorities as a form of assessing academic–clinical partnership alignment. Simulated application indicates MAUA may be successfully utilized as an evidence-based methodological framework. The presented example is illustrative of the wide-spanning potential for this approach in different contexts, as predicted and recommended by experts in the field. Evaluators are encouraged to collaborate in new ways and strive to produce tangible, solution-oriented approaches to address key challenges and demonstrate the value of sound evaluation practices.

Use of life cycle assessment (LCA) to advance optimisation of radiological protection and safety

Life cycle assessment (LCA) is a modelling technique used to determine the cradle-to-grave environmental and human health impacts from the production of a good or the provision of a service. Radiological protection may benefit from employing tools like LCA to obtain a broader perspective and enable comparison with analyses of non-radiological systems. Despite structural similarities to other well-established decision-aiding techniques (DATs), the impact assessment within LCA (i.e. LCIA) is not commonly used in the optimisation of radiological protection process. This paper provides a brief review of LCA, including LCIA, along with more traditional DATs (such as multi-attribute utility analysis) used in the optimisation process for comparison. Basic concrete shielding was considered as a simple, illustrative example; concrete attenuates emissions from a radiation source but is also associated with a financial cost as well as costs with respect to energy, material, and water use. LCA offers quantification of these and other key resources (termed ‘impact categories’). Ultimately, we offer that, depending on the circumstance, LCA can be a useful tool in radiological protection decision-making, complementing existing techniques.

Study of radiation protection vestments for maintenance of mobile nuclear power plants

Most radiation exposure to personnel comes from inspection, maintenance, and repair within the reactor compartment. The objective of this paper was to discover the garment that, at the same time, presents the best result for the attenuation of ionizing radiation, as well as good ergonomics for the maintenance professional of mobile nuclear plants. For this, market research was carried out and, as a result, nine Radiation Protection Vestments (VPRs) were found, from five different manufacturers and from three countries, the United States, Japan and China; and which are feasible to be acquired. To choose the VPR, the optimization techniques of CIPR 55 were used: Multi-Attribute Utility Analysis and Multi-Criteria Outranking Analysis. Based on the information provided by the manufacturers, five attributes were chosen for comparison: protection cost, percentage of ionizing radiation attenuation, weight, discomfort, and surface decontamination of the vestment. To verify the robustness of the analytical solution, the values of the scaling constants were re-calculated, where it was observed that the analytical solution found is strongly influenced when the protection cost is changed, as it is the highest cost VPR among all those surveyed. The VPR chosen by both optimization techniques was the STEMRAD 360, which has the highest attenuation of ionizing radiation, as well as being the VPR with greater emphasis on ergonomics.

Disutility Entropy in Multi-attribute Utility Analysis

In this paper, we present an alternative formulation of utility entropy called disutility entropy. Previous entropy measurements in the literature use utility density function in maximum entropy formulations. Also, in most of the cases, the sign of the cross derivative of utility functions makes it impossible to apply utility entropy for more than one attribute cases. To simplify entropy measurement and relieve some burden of this task, in this paper, we present how to use multiattribute utility functions in utility entropy formulation. We show the applicability of our proposed approach and how to apply the disutility entropy approach with given constraints to single-attribute, bi-attribute, and multiattribute utility functions. Therefore, the usefulness and feasibility of the proposed method in multiattribute utility theory field is improved. We finally discuss and interpret the application of maximum disutility entropy through several examples to illustrate the new proposed approach.

Factors influencing the consideration of Public-Private Partnerships (PPP) for smart city projects: Evidence from Hong Kong

Smart cities are emerging in most parts of the world. The cost-benefit analysis of such initiatives should include an unbiased consideration of potential procurement modes, especially when a substantial investment is entailed to scale up projects to the city level. Despite the enticing trend of public private partnerships (PPPs), city governments should evaluate the available options using an objective approach such as Multi-Attribute Utility Analysis (MAUA). The technique takes into account prioritized assessment criteria (which are tailor-made for smart city projects) and the relative utilities of the procurement options in meeting the criteria.The methodology of MAUA is demonstrated through a questionnaire survey and a focus group meeting involving public and private sector practitioners, and applied to 8 types of common smart city projects in Hong Kong, which is one of the metropolises earmarked to become a smart city by putting concepts into practice. Results show that not all projects are best suited to PPP and that there may be divergent views between the public and private sectors, with possibilities for a compromised decision which both sectors would accept.

Traditional Faculty Meeting Style is Not Conducive to Group Decision Making

Traditional group meeting style in an organizational setting is a common platform for collaborative decision-making. This setting can be disruptive and fraught with bias, resulting in unhealthy conflict and failure to accomplish the goals of the meeting. The outcome of said meetings can offer false representation of support for a given decision. The author sought out to devise a new decision-making model that will attempt to remove unwanted bias from the decision-making process. Common attributes that result in bias include the lack of information and under time constraints, decisions made without enough background information and in a perceived limited time frame. The makeup of the organization meetings with supervisors, subordinates, mentors can create bias when votes are verbal, not anonymous. This paper explores problems with group decision-making and why the current method provides a false representation of support. Current methods for group decision making are defined and include the Naturalistic Decision-Making model, Multi-Attribute Utility Analysis, and Decision Analysis. The Nominal Group and Delphi techniques are explored as options available, but not successful in this situation. Based on the current models, techniques, and the needs of the organization meetings, a successful alternative to decision-making in a group environment is characterized and explained.

Offsite Manufacturing in the Construction Industry for Productivity Improvement

Offsite manufacturing (OSM) is believed to be an alternative means of improving construction productivity. However, OSM has attracted limited attention from researchers and industry stakeholders, particularly in developing countries. Therefore, this study considers the key factors hindering the industry-wide adoption of OSM in the Cambodian context. A survey conducted with 75 construction practitioners asked respondents to quantify the level of influence from 30 constraints pertaining to OSM. Multi-attribute utility and correlation coefficient analyses were used to statistically analyze the data. Six broad categories of constraints to adopting OSM underlie the challenges facing the local industry: project planning and methodology, construction cost, construction industry and culture, skill and shortage, supply chain and logistics, and construction site operations. The findings may be useful for construction engineering professionals seeking ways to improve construction productivity performance by implementing OSM as an alternative technique in developing countries.

Distribution network reinforcement planning in uncertain environment using stochastic multi-attribute utility analysis

This paper considers a stochastic multiple criteria decision-making problem in power distribution system reinforcement planning. The problem with exhaustive set of alternatives, with different types of trade-offs among stochastic criteria, has been solved using the novel analytical methodology. The proposed methodology is based on discrete convolution of criteria probability distribution functions and OWA operators, modelling different types of criteria aggregation. After the new, aggregated probability distributions have been built for every alternative, they are ranked by the overall expected utility. The methodology allows the usage of compensatory aggregation, which is more suitable for conflicting criteria or the human aggregation behaviour. Finally, an example of decision on the network reinforcement of IEEE 34 bus test feeder illustrates the efficiency of this method.

Comparison of proliferation resistance among natural uranium, thorium–uranium, and thorium–plutonium fuels used in CANada Deuterium Uranium in deep geological repository by combining multiattribute utility analysis with transport model

Abstract The proliferation resistance (PR) of Th/U and Th/Pu fuels used in CANada Deuterium Uranium for the deep geological repository was assessed by combining the multiattribute utility analysis proposed by Chirayath et al., 2015 [1] with the transport model of radionuclides in the repository and comparing with that of the used natural U fuel case. It was found that there was no significant advantage for Th/U and Th/Pu fuels from the viewpoint of the PR in the repository. It was also found that the PR values for used nuclear fuels in the repository of Th/U, Th/Pu, and natural U was comparable with those for enrichment and reprocessing facilities in the pressurized water reactor (PWR) nuclear fuel cycle. On the other hand, the PR values considering the transport of radionuclides in the repository were found to be slightly smaller than those without their transport after the used nuclear fuels started dissolving after 1,000 years.

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS)-entropy Methodology for Inherent Safety Design Decision Making Tool

Inherently Safer Design (ISD) concept has been recognized as a way to achieve safer operation and economically attractive for the process plant. However, the challenges in selecting between ISD alternatives are the need to satisfy conflicting objectives. Therefore, there is the need for a multi-criteria decision-making tool that can make a reliable, coherent and defensible decision. The objective of this paper is to illustrate the use of the TOPSIS-entropy method as a decision-making tool to evaluate the trade-off of ISD alternatives. Entropy method was included in TOPSIS calculation to remove the subjectivity problem during the weight scoring process for attributes. This methodology has been applied to identify the best ISD alternatives for methyl isocyanate storage at West Virginia fertilizer production plant. The results show that the rank obtained for ISD alternatives influenced by the weight value that indicate the priority given to the attributes. The Du Pont method has been identified as the best option when higher priority given to the attributes under external/regulatory pressure and the existing methodology with inventory reduction has been identified as the best option when higher priority given to the attributes under internal/cost pressure. The results obtained using TOPSIS-entropy method are congruent with the results reported in the previous work using Multi Attribute Utility Analysis proves that this method can be used to resolve ISD conflicts effectively. More than that, the capability of TOPSIS to deal with different types of weight estimation techniques gives an added value to this methodology.

Analysis of measures to enhance safeguards, and proliferation resistance in thorium based fuel fabrication plants

The presence of high energy gamma rays emitted by U232, which is always associated in ppm quantities with reprocessed U233, lends robustness or physical protection to the thorium fuel cycle. India is currently setting up a thorium based fuel cycle for its Advanced Heavy Water Reactor (AHWR). Identification and deployment of suitable extrinsic measures for fuel fabrication facilities would help in strengthening overall proliferation resistance. The extrinsic measures proposed in this paper include several measures which have been identified for the first time. A quantitative assessment of the contribution of these measures to overall safeguardability of the fuel fabrication plant has been carried out. Multi Attribute Utility Analysis (MAUA) has been used to evaluate the Proliferation Resistance (PR) value for two hypothetical facilities, one employing none of these measures and the other employing some or all of these measures. The analysis is based on the expert opinion of designers, operators, quality control managers and implementers of safeguards in fuel cycle facilities. Sensitivity analysis for all the proposed measures has also been carried out to study the effect of the influence of individual measures on the overall proliferation resistance of the fuel fabrication plant. The analysis ranks various safeguards measures based on the importance factor of a measure which is defined as the ratio of overall proliferation resistance with and without the measure. Important measures identified based on ranking are near real time monitoring, automation, safeguards-by-design, dynamic nuclear material accounting, and plant imaging.

Application of multi attribute utility theory in multiple releases of software

One of the important applications of software reliability models is the determination of software release time. Most of the existing studies on this topic use models based on non homogeneous Poisson process with a bounded mean value function. Multi up gradation based software reliability growth model is developed for successive release modelling and analysis. Based on this model, maximum fault removal for upgraded software and optimal release time of upgraded software are investigated as well. This paper proposes a new practical method for determining when to stop software testing considering failure intensity and cost as two factors simultaneously. This issue has been widely known as the optimal release problem of software product. The proposed new decision model based on multi-attribute utility analysis is tested on the real world data sets. In addition, the proposed decision model can help companies to make a rational decision on the optimal timing of the software.

Release time problem with multiple constraints

Quality of software system generally depends on how much time testing takes and what testing methodologies are used. One attribute of quality is reliability which can be increased by removing more faults from the software and this can be done by spending more time on testing. However, spending more time on testing will increase cost of the software development process. On the other hand, if testing time is too short, testing cost of software may be reduced but it will increase the chance of getting unreliable software and customers may not take higher risk of buying unreliable software. Highly competitive market conditions have forced developers to offer highly reliable products to the users. Software warranty is one such indicator used by the users to judge its reliability with the perception that a longer warranty period indicates higher reliability. Software warranty is a tool which provides assurance about the quality. Warranty cost may be reduced by providing more reliable product. Therefore software reliability, testing, warranty period and cost needs to be considered jointly. In this paper, we propose a new method to estimate the optimal software release time of a software with warranty under imperfect debugging environment by using Multi Attribute Utility Theory. More precisely, three significant attributes, namely Reliability, Cost and Detection rate indicator are used to determine the optimal release time of software under warranty. The proposed new decision model based on multi-attribute utility analysis is tested on the real world data set.

ニューラルネットワークを用いた集団多属性効用分析

In this paper, we deal with group multiattribute utility analysis incorporating preferences of multiple interested individuals.Since it is difficult to repeatedly ask them questions for determining parameters of a multiattribute utility function, we gather preference information of them by asking not difficult questions to answer, and develop a method for selecting an alternative consistent with the preference information. For a given set of single-attribute utility functions, assuming multiattribute utility functions to be in the multiplicative form, we evaluate trade-off between attributes by utilizing neural networks. Using the preference information actually gathered in an application study[12], we verify the effectiveness of the proposed method.

Optimization of Size and Encapsulation Efficiency of 5-FU Loaded Chitosan Nanoparticles by Response Surface Methodology

The objective of this study was to optimize the particle size and encapsulation efficiency of chitosan nanoparticles loaded with 5-Fluorouracil (5-FU) by response surface methodology. Nanoparticles were prepared by ionic gelation method from chitosan and penta sodium triphosphate (TPP) at different combinations of chitosan viscosity, chitosan concentration and chitosan/TPP mass ratio according to the Box-Behnken experimental design. The particle size and encapsulation efficiency of prepared particles were measured by dynamic light scattering and UV spectroscopy, respectively, and the obtained data were subjected to multiple linear regression analysis followed by multi-attribute utility analysis to obtain a model for prediction of the optimum response. The optimum conditions for the production of 5-FU loaded chitosan nanoparticles were found to be low viscosity chitosan 0.5-1 mg/mL, middle viscosity chitosan 0.5-0.8 mg/mL and high viscosity chitosan 0.5-0.75 mg/mL and chitosan/TPP mass ratio of 4 or 6, yielding nanoparticles at the average diameter range of 114-188 nm and encapsulation efficiencies between 42-55%.

Use of multi-criteria decision analysis in regulatory alternatives analysis: A case study of lead free solder

Regulators are implementing new programs that require manufacturers of products containing certain chemicals of concern to identify, evaluate, and adopt viable, safer alternatives. Such programs raise the difficult question for policymakers and regulated businesses of which alternatives are "viable" and "safer." To address that question, these programs use "alternatives analysis," an emerging methodology that integrates issues of human health and environmental effects with technical feasibility and economic impact. Despite the central role that alternatives analysis plays in these programs, the methodology itself is neither well-developed nor tailored to application in regulatory settings. This study uses the case of Pb-based bar solder and its non-Pb-based alternatives to examine the application of 2 multi-criteria decision analysis (MCDA) methods to alternatives analysis: multi-attribute utility analysis and outranking. The article develops and evaluates an alternatives analysis methodology and supporting decision-analysis software for use in a regulatory context, using weighting of the relevant decision criteria generated from a stakeholder elicitation process. The analysis produced complete rankings of the alternatives, including identification of the relative contribution to the ranking of each of the highest level decision criteria such as human health impacts, technical feasibility, and economic feasibility. It also examined the effect of variation in data conventions, weighting, and decision frameworks on the outcome. The results indicate that MCDA can play a critical role in emerging prevention-based regulatory programs. Multi-criteria decision analysis methods offer a means for transparent, objective, and rigorous analysis of products and processes, providing regulators and stakeholders with a common baseline understanding of the relative performance of alternatives and the trade-offs they present.

The optimisation of maintenance service levels to support the product service system

The dematerialising concept has formed a new management model: the product service system (PSS). PSS means that enterprises have changed the management concept of ‘product foremost and service second’ to ‘service-based product’ in design products, and the products are the tools produced and innovated for service. Therefore, the physical logistical service replaces the virtual service. However, during the transformation, the product service system also needs to emphasise cost, customers’ satisfaction and environmental protection. This study analysed different types of integrated maintenance service and used multi-attribute utility analysis to discuss the overall utility of maintenance service. The operation cost, CO 2 emission and service satisfaction indicators of different maintenance service models were used as decision variables to determine the optimal maintenance system. Finally, a case study is described to demonstrate this research.

Disassembly and Reassembly Sequence Planning Tradeoffs Under Uncertainty for Product Maintenance

The problem addressed in this paper is disassembly sequence planning for the purposes of maintenance or component upgrading, which is an integral part of the remanufacturing process. This involves disassembly, component repair or replacement, and reassembly. Each of these steps incurs cost as well as the probability of damage during the process. This paper presents a method for addressing these tradeoffs, as well as the uncertainty associated with them. A procedure for identifying the best sequence of disassembly operations for maintenance and/or component upgrade is presented. It considers both disassembly and reassembly costs and uncertainties. Graph-based integer linear programming combined with multi-attribute utility analysis is employed to identify the best set of tradeoffs among (a) disassembly time (and resulting cost) under uncertainty, (b) the probability of not incurring damage during disassembly, (c) reassembly time (and resulting cost), and (d) the probability of not incurring damage during reassembly. An example of a solar heating system is used to illustrate the method.

An Empirical Evaluation of Training Using Multi-attribute Utility Analysis

Purpose This paper aims to develop and apply a multi-attribute utility analysis model (MAU) to assess the benefits of HRM interventions as an alternative to the traditional utility analysis method.

Multiattribute utility analysis for policy selection and financing for the preservation of the forest

In this paper, we examine effective policies for financing and activities for the preservation of the forest on Mount Ryuoh in the city of Higashi-Hiroshima by multiattribute utility analysis. In multiattribute utility analysis, we deal with decision making problems with multiple attributes and select the most effective solution among several alternatives by deriving preference of the decision maker. Although in our decision making problem, the decision maker is a representative of a hypothetical nonprofit organization established for the preservation of the forest, the decision maker gives serious consideration to intentions of several groups of people receiving the benefit from the mountain, and then from this viewpoint, our problem can be interpreted as a group decision making problem.