Relevant bibliographies by topics / Leveraging Multi-Attribute Utility Theory

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Academic literature on the topic 'Leveraging Multi-Attribute Utility Theory'

Author: Grafiati
Published: 7 June 2025
Last updated: 26 June 2025

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Journal articles on the topic "Leveraging Multi-Attribute Utility Theory"

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Lakshmi, Narasimhan Srinivasagopalan. "A Cloud-Based Framework for Personalized Health Insurance Recommendations: Leveraging Multi-Attribute Utility Theory for Enhanced User Experience." European Journal of Advances in Engineering and Technology 10, no. 12 (2023): 99–107. https://doi.org/10.5281/zenodo.14274707.

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The Health Insurance Marketplace aims to simplify the selection process for consumers by allowing them to compare insurance plans based on cost, coverage, and quality. However, existing web-based tools lack personalized recommendation capabilities that cater to individual user needs. This paper introduces a novel cloud-based framework designed to provide customized health insurance plan recommendations using Multi-Attribute Utility Theory (MAUT). Our framework enables users to evaluate plans on key parameters, including premium, co-pay, deductibles, co-insurance, and maximum benefits, offering a comprehensive comparison of coverage and cost options tailored to their preferences. To address inconsistencies in plan representation and data formats across providers, we developed a standardized plan schema that enables seamless data integration through Data as a Service (DaaS). Implemented as a Software as a Service (SaaS) solution, the framework ranks insurance plans based on user-defined criteria, delivering intuitive and personalized recommendations. Experimental results demonstrate the framework’s accuracy and efficiency in generating relevant plan suggestions, significantly improving the user experience in selecting optimal health insurance coverage. This cloud-based solution paves the way for more accessible and informed decision-making in the Health Insurance Marketplace, bridging the gap between complex plan offerings and consumer needs.
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Researcher. "A Cloud-Based Framework for Personalized Health Insurance Recommendations: Leveraging Multi-Attribute Utility Theory for Enhanced User Experience." European Journal of Advances in Engineering and Technology 10, no. 12 (2023): 99–107. https://doi.org/10.5281/zenodo.14598952.

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The Health Insurance Marketplace aims to simplify the selection process for consumers by allowing them to compare insurance plans based on cost, coverage, and quality. However, existing web-based tools lack personalized recommendation capabilities that cater to individual user needs. This paper introduces a novel cloud-based framework designed to provide customized health insurance plan recommendations using Multi-Attribute Utility Theory (MAUT). Our framework enables users to evaluate plans on key parameters, including premium, co-pay, deductibles, co-insurance, and maximum benefits, offering a comprehensive comparison of coverage and cost options tailored to their preferences. To address inconsistencies in plan representation and data formats across providers, we developed a standardized plan schema that enables seamless data integration through Data as a Service (DaaS). Implemented as a Software as a Service (SaaS) solution, the framework ranks insurance plans based on user-defined criteria, delivering intuitive and personalized recommendations. Experimental results demonstrate the framework's accuracy and efficiency in generating relevant plan suggestions, significantly improving the user experience in selecting optimal health insurance coverage. This cloud-based solution paves the way for more accessible and informed decision-making in the Health Insurance Marketplace, bridging the gap between complex plan offerings and consumer needs.
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Munawarah, Munawarah, Wahyu Fuadi, and Hafizh Al Kautsar Aidilof. "Student Learning Style Decision-Making System Using the Multi-Attribute Utility Theory Method at SMA Negeri 1 Jangka." International Journal of Engineering, Science and Information Technology 5, no. 2 (2025): 320–27. https://doi.org/10.52088/ijesty.v5i2.842.

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Education plays a vital role in shaping individual development and national progress. One key factor influencing learning effectiveness is students' learning styles, which determine how individuals absorb, organize, and process information. Understanding these differences is crucial for designing effective teaching methods. This research develops a Decision Support System (DSS) to determine student learning styles at SMA Negeri 1 Jangka using the Multi-Attribute Utility Theory (MAUT) method. MAUT is chosen for its ability to evaluate multiple criteria, convert them into numerical values, and systematically identify the most suitable learning approach. The alternatives in this study include Project Based Learning (PBL), Problem-Based Learning (PrBL), Inquiry-Based Learning (IBL), Discovery Learning (DL), and Contextual Teaching and Learning (CTL). The MAUT analysis considers five criteria: student activeness, material understanding, collaboration, initiative and creativity, and teacher-student communication. The research stages include literature study, data collection, system and database design, MAUT implementation, and system evaluation. The results, based on MAUT calculations, show that Inquiry-Based Learning (IBL) scores the highest at 13.611, followed by Discovery Learning (DL) at 13.018, Problem-Based Learning (PrBL) at 12.975, Contextual Teaching and Learning (CTL) at 12.929, and Project Based Learning (PBL) at 12.558. This system assists educators in designing personalized learning strategies that align with students' strengths. Leveraging data-driven analysis enhances education quality, fosters a student-centred learning environment, and improves academic performance and lifelong learning habits.
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Eldesouky, Mohamed, Marcus Vinicius Pereira Pessoa, and Vlad Stefanovici. "LEVERAGING MISSION SOLUTION CONFIGURATION THROUGH MBSE AND TRADESPACE EXPLORATION." INCOSE International Symposium 34, no. 1 (2024): 2028–47. http://dx.doi.org/10.1002/iis2.13254.

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AbstractThales is a worldwide leader in innovative radar and mission solution systems used by naval ships. As the demand for personalized products increased through time, Thales shifted from a project‐oriented to a product‐oriented approach. This shift aims to capitalize on variants, minimize customization, and streamline operations. In this context, Thales established a mission solution configuration process (SCP) to facilitate the selection of product variants to compose a system during the bidding phase. However, the current SCP has limitations, constraining exploration and integration with engineering processes and system data. Consequently, the proposed systems sometimes fall short of the most optimal solution the client could get. Therefore, the objective of this work is to develop and validate an improved mission solution configuration process to streamline the creation and selection of product variants at Thales, particularly during the bidding phase, to better meet client needs and operational requirements. This method integrates Model‐Based Systems Engineering (MBSE) and Tradespace Exploration (TSE), utilizing ARCADIA as the methodology and Capella as the tool. A descriptive model is generated for analytical purposes within TSE, employing Multi‐Attribute‐Utility‐Theory (MAUT) and Pareto‐Optimization for evaluating and selecting optimal mission solution variants. Validation was conducted through a Coast Guard mission case study involving 125 solution variants, revealing Pareto‐optimal solutions balancing performance and cost. This method enhances the current configuration process by aligning client and operational needs with Thales's sales and product teams, ensuring accurate interpretation of requirements and minimizing information inconsistencies. The case study results identify technological gaps in variant designs, guiding research and development efforts towards subsystems or components with significant impact on system performance.
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Bhola, Prabha, Alexandros-Georgios Chronis, Panos Kotsampopoulos, and Nikos Hatziargyriou. "Business Model Selection for Community Energy Storage: A Multi Criteria Decision Making Approach." Energies 16, no. 18 (2023): 6753. http://dx.doi.org/10.3390/en16186753.

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This paper explores business models for community energy storage (CES) and examines their potential and feasibility at the local level. By leveraging Multi Criteria Decision Making (MCDM) approaches and real-world case studies in Europe and India, it presents insights into CES deployment opportunities, challenges, and best practices. Different business models, including community energy cooperatives, utility–community partnerships, demand response, energy services, and market mechanisms, are analyzed. The proposed method combines the MCDM method PROMETHEE II with the fuzzy set theory to obtain a complete CES business model ranking, addressing project uncertainties. The analysis emphasizes CES’s role in balancing local renewable energy supply and demand, facilitating energy sharing, and achieving energy independence. Findings prioritize models like Community Cooperative, Energy Arbitrage, and Energy Arbitrage Peak Shaving for CES with renewables. Environmental benefits include reduced diesel use and greenhouse gas emissions. Efficient cooperatives are advocated to recover costs and enable competitive energy prices. The paper highlights the need for novel value propositions to boost the energy transition in local communities. This research contributes to the discourse on CES business models, fostering knowledge exchange and promoting effective strategies for sustainable energy systems.
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Rai, Anil Kumar, Arun Kumar Maurya, Ritesh Kumar Sharma, and Mansi Singh. "Modelling Analysis and Characteristics of Multi-Level Inverter for Integrating Solar PV System to Grid." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 125, no. 2 (2024): 82–92. https://doi.org/10.37934/arfmts.125.2.8292.

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This paper investigates the implementation of a cascaded H-bridge multi-level inverter in a single-phase grid-connected solar photovoltaic (PV) system to address harmonic distortion challenges in DC-to-AC power conversion. The primary objective is to enhance power quality and system efficiency by leveraging the inverter's ability to reduce harmonics through power sharing and a lower switching frequency. A Simulink model is developed to evaluate the proposed system's performance, incorporating a unipolar Pulse Width Modulation (PWM) control strategy and an LCL filter for effective harmonic mitigation. The system employs Maximum Power Point Tracking (MPPT) based on the Perturb and Observe (P&O) algorithm, combined with Synchronous Reference Frame Theory-Phase Disposition PWM (SRFT-PDPWM) for optimal control. The proposed inverter ensures precise synchronization between the grid and inverter frequencies, achieving a Total Harmonic Distortion (THD) below 5%. Simulation results demonstrate the system's robust responsiveness to variations in solar irradiance, with increased irradiance leading to further reductions in THD and improved power quality. These findings validate the proposed inverter's capability to deliver high-quality, efficient power under varying environmental conditions, aligning with global objectives for integrating clean and sustainable energy into utility networks.
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Syau, Yu-Ru, En-Bing Lin, and Churn-Jung Liau. "An Order-Theoretic Study on Formal Concept Analysis." Axioms 12, no. 12 (2023): 1099. http://dx.doi.org/10.3390/axioms12121099.

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This paper employs an order-theoretic framework to explore the intricacies of formal concepts. Initially, we establish a natural correspondence among formal contexts, preorders, and the resulting partially ordered sets (posets). Leveraging this foundation, we provide insightful characterizations of atoms and coatoms within finite concept lattices, drawing upon object intents. Expanding from the induced poset originating from a formal context, we extend these characterizations to discern join-irreducible and meet-irreducible elements within finite concept lattices. Contrary to a longstanding misunderstanding, our analysis reveals that not all object and attribute concepts are irreducible. This revelation challenges the conventional belief that rough approximations, grounded in irreducible concepts, offer sufficient coverage. Motivated by this realization, the paper introduces a novel concept: rough conceptual approximations. Unlike the conventional definition of object equivalence classes in Pawlakian approximation spaces, we redefine them by tapping into the extent of an object concept. Demonstrating their equivalence, we establish that rough conceptual approximations align seamlessly with approximation operators in the generalized approximation space associated with the preorder corresponding to a formal context. To illustrate the practical implications of these theoretical findings, we present concrete examples. Furthermore, we delve into the significance and potential applications of our proposed rough conceptual approximations, shedding light on their utility in real-world scenarios.
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Şenel, Güzide. "An Innovative Algorithm Based on Octahedron Sets via Multi-Criteria Decision Making." Symmetry 16, no. 9 (2024): 1107. http://dx.doi.org/10.3390/sym16091107.

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Octahedron sets, which extend beyond the previously defined fuzzy set and soft set concepts to address uncertainty, represent a hybrid set theory that incorporates three distinct systems: interval-valued fuzzy sets, intuitionistic fuzzy sets, and traditional fuzzy set components. This comprehensive set theory is designed to express all information provided by decision makers as interval-valued intuitionistic fuzzy decision matrices, addressing a broader range of demands than conventional fuzzy decision-making methods. Multi-criteria decision-making (MCDM) methods are essential tools for analyzing and evaluating alternatives across multiple dimensions, enabling informed decision making aligned with strategic objectives. In this study, we applied MCDM methods to octahedron sets for the first time, optimizing decision results by considering various constraints and preferences. By employing an MCDM algorithm, this study demonstrated how the integration of MCDM into octahedron sets can significantly enhance decision-making processes. The algorithm allowed for the systematic evaluation of alternatives, showcasing the practical utility and effectiveness of octahedron sets in real-world scenarios. This approach was validated through influential examples, underscoring the value of algorithms in leveraging the full potential of octahedron sets. Furthermore, the application of MCDM to octahedron sets revealed that this hybrid structure could handle a wider range of decision-making problems more effectively than traditional fuzzy set approaches. This study not only highlights the theoretical advancements brought by octahedron sets but also provides practical evidence of their application, proving their importance and usefulness in complex decision-making environments. Overall, the integration of octahedron sets and MCDM methods marks a significant step forward in decision science, offering a robust framework for addressing uncertainty and optimizing decision outcomes. This research paves the way for future studies to explore the full capabilities of octahedron sets, potentially transforming decision-making practices across various fields.
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Peres da Silva, Rafael, Chayaporn Suphavilai, and Niranjan Nagarajan. "TUGDA: task uncertainty guided domain adaptation for robust generalization of cancer drug response prediction from in vitro to in vivo settings." Bioinformatics 37, Supplement_1 (2021): i76—i83. http://dx.doi.org/10.1093/bioinformatics/btab299.

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Abstract Motivation Large-scale cancer omics studies have highlighted the diversity of patient molecular profiles and the importance of leveraging this information to deliver the right drug to the right patient at the right time. Key challenges in learning predictive models for this include the high-dimensionality of omics data and heterogeneity in biological and clinical factors affecting patient response. The use of multi-task learning techniques has been widely explored to address dataset limitations for in vitro drug response models, while domain adaptation (DA) has been employed to extend them to predict in vivo response. In both of these transfer learning settings, noisy data for some tasks (or domains) can substantially reduce the performance for others compared to single-task (domain) learners, i.e. lead to negative transfer (NT). Results We describe a novel multi-task unsupervised DA method (TUGDA) that addresses these limitations in a unified framework by quantifying uncertainty in predictors and weighting their influence on shared feature representations. TUGDA’s ability to rely more on predictors with low-uncertainty allowed it to notably reduce cases of NT for in vitro models (94% overall) compared to state-of-the-art methods. For DA to in vivo settings, TUGDA improved over previous methods for patient-derived xenografts (9 out of 14 drugs) as well as patient datasets (significant associations in 9 out of 22 drugs). TUGDA’s ability to avoid NT thus provides a key capability as we try to integrate diverse drug-response datasets to build consistent predictive models with in vivo utility. Availabilityand implementation https://github.com/CSB5/TUGDA. Supplementary information Supplementary data are available at Bioinformatics online.
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HengLi Yang, and HsiaoFang Yang. "Recommendation Mechanism Based on Multi-attribute Utility Theory." International Journal of Digital Content Technology and its Applications 5, no. 3 (2011): 373–82. http://dx.doi.org/10.4156/jdcta.vol5.issue3.37.

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Dissertations / Theses on the topic "Leveraging Multi-Attribute Utility Theory"

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Stefancik, John. "Demand forecasting using Monte Carlo Multi-Attribute Utility Theory." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104825.

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Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 173-176).<br>Volatile commodity prices over the past decade, environmentally-focused policy initiatives and new technology developments have forced manufacturers to consider the idea of substituting towards alternative materials in order meet both consumer and societal needs. The threat of substitution has created the need for manufacturing firms and other members of the supply chain to have the ability to understand the implications of substitution on future product market shares and overall raw material demand. This thesis demonstrates how Multi-Attribute Utility Theory (MAUT) can be extended to the group level to forecast future market shares by applying a distribution to the attribute weights and using a Monte Carlo simulation to capture the choices made by a heterogeneous set of decision makers. Unlike established demand forecasting techniques, such as discrete choice models, this methodology requires only a few data points from a handful of expert interviews and allows for systematic changes of preferences over time. Furthermore, the Monte Carlo MAUT methodology utilizes both revealed preference and stated preference data by integrating the two data types through a response surface methodology. Two case studies on underground distribution and overhead distribution power cables are explored in order to illustrate how the Monte Carlo MAUT methodology can be successfully applied in cases where there are diverse product types, limited numbers of decisions makers and historical market share data is sparse. Each case study illustrates how Monte Carlo MAUT can, on a regional basis, provide key insights into the impacts of changing commodity prices, changing product attribute levels, varying new technology learning rates and changing consumer preferences over time. Furthermore, an example of how Monte Carlo MAUT can be utilized to help policymakers evaluate the advantages, disadvantages and overall impact of different policy schemes within an environmental context is provided. Private firms and public governments alike can utilize Monte Carlo MAUT to improve their understanding of how market shares are likely to change over time, and more importantly, the key decisions needed on each party's behalf in order to maximize societal well-being.<br>by John Stefancik.<br>S.M. in Technology and Policy
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Wang, Chen. "Modeling multi-attribute utility theory with object-oriented programming." Master's thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-01122010-020130/.

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Vajda, Joshua Lewis. "Evaluation and Selection of Oil Shale Extraction Methods Using Multi-Attribute Utility Theory." Thesis, The George Washington University, 2021. http://pqdtopen.proquest.com/#viewpdf?dispub=28256190.

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In the United States, on-site (in-situ) oil shale extraction methods are underutilized, leading to a potential loss of $20 billion per year in profit. On-site oil shale extraction methods are not considered when discussing large-scale oil shale extraction operations. Off-site (ex-situ) extraction remains the only commercialized method, but on-site extraction is showing considerable promise. The on-site methods allow for the exploitation of deeper oil shale prospects, which have the potential of producing up to 1.32 trillion barrels of oil. Oil shale is an unconventional hydrocarbon resource that must be considered part of the overall energy solution. There are two general methods for extracting oil shale resources: off-site extraction and on-site extraction. The off-site method consists of surface mining and above ground heating. The on-site methods consist of well drilling, well completion, and underground heating. Due to their technical differences, a comparison of the methods is difficult. This praxis seeks to inform the selection of oil shale extraction methods using a multi-attribute utility function as part of a decision tool. The tool consists of three components: the oil production model, the cost model, and the decision model. The practical application of the tool is to bring on-site extraction methods into the conversation. The Piceance Basin, located in western Colorado, is used to show the application of the tool in the field. With the ability to evaluate different extraction methods and process-heating options using the decision tool, the exploitation of more oil shale is possible. Multi-criteria decision-making methods have seen increased use in process industries. Decision making in mining and offshore oil and gas exploration provides useful insights into how decisions are made and how decision analysis could be used for oil shale projects. When evaluating distinct oil shale extraction alternatives, a decision tool, built around multi-attribute utility theory, simulation, and regression analysis provides the best vehicle for systematic decision making.
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Chang, Jin O. "A generalized decision model for naval weapon procurement multi-attribute decision making /." [Tampa, Fla.] : University of South Florida, 2005. http://purl.fcla.edu/fcla/etd/SFE0001025.

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Phillips, Steve. "OVID-BV : optimising value in decision making for best value in the UK social housing sector." Thesis, Loughborough University, 2007. https://dspace.lboro.ac.uk/2134/3530.

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The Governments' promotion and support of Best Value within the Social Housing Sector has been a prime catalyst in the move by Registered Social Landlord's [RSL's] away from the traditional culture of acceptance of the lowest bid towards consideration of both price and quality criteria as a basis for contractor selection. Manifestly this radical change in the way the sector procures its construction services has forced many of its stakeholders to undergo significant cultural and organisational changes within a relatively short period of time, and problems have developed during this transitional period that have affected the efficiency of the best value process. This research traced the root causes of these problems and its overarching aim was to develop an approach which will enable RSL's and their stakeholders to streamline the best value tender analysis procedure thereby allowing tenders to be dealt with effectively and efficiently whilst also creating a transparent and auditable decision making process. The approach has been established using a mixed methods research methodology utilising; case studies, surveys, rational decision analysis and system evaluation. The main output of the research is the development of a support tool known by the acronym OVID-BV which aids the multi objective decision making process. The underlying rationale for the support tool is based on the innovative use of uncertainty in decision making and the functionality of the tool uses a combination of the analytical hierarchy process (AHP), multi attribute utility theory (MAUT) and whole life costing (WLC).
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Petrillo, Jennifer. "Development and validation of the EXACT-U* to report utilities for COPD exacerbations : a comparison of statistical inference and multi-attribute utility theory method." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549744.

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Pudney, Steven Grant. "Asset renewal decision modelling with application to the water utility industry." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/40933/1/Steven_Pudney_Thesis.pdf.

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Reliable infrastructure assets impact significantly on quality of life and provide a stable foundation for economic growth and competitiveness. Decisions about the way assets are managed are of utmost importance in achieving this. Timely renewal of infrastructure assets supports reliability and maximum utilisation of infrastructure and enables business and community to grow and prosper. This research initially examined a framework for asset management decisions and then focused on asset renewal optimisation and renewal engineering optimisation in depth. This study had four primary objectives. The first was to develop a new Asset Management Decision Framework (AMDF) for identifying and classifying asset management decisions. The AMDF was developed by applying multi-criteria decision theory, classical management theory and life cycle management. The AMDF is an original and innovative contribution to asset management in that: · it is the first framework to provide guidance for developing asset management decision criteria based on fundamental business objectives; · it is the first framework to provide a decision context identification and analysis process for asset management decisions; and · it is the only comprehensive listing of asset management decision types developed from first principles. The second objective of this research was to develop a novel multi-attribute Asset Renewal Decision Model (ARDM) that takes account of financial, customer service, health and safety, environmental and socio-economic objectives. The unique feature of this ARDM is that it is the only model to optimise timing of asset renewal with respect to fundamental business objectives. The third objective of this research was to develop a novel Renewal Engineering Decision Model (REDM) that uses multiple criteria to determine the optimal timing for renewal engineering. The unique features of this model are that: · it is a novel extension to existing real options valuation models in that it uses overall utility rather than present value of cash flows to model engineering value; and · it is the only REDM that optimises timing of renewal engineering with respect to fundamental business objectives; The final objective was to develop and validate an Asset Renewal Engineering Philosophy (AREP) consisting of three principles of asset renewal engineering. The principles were validated using a novel application of real options theory. The AREP is the only renewal engineering philosophy in existence. The original contributions of this research are expected to enrich the body of knowledge in asset management through effectively addressing the need for an asset management decision framework, asset renewal and renewal engineering optimisation based on fundamental business objectives and a novel renewal engineering philosophy.
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Casanovas-Rubio, Maria del Mar, Carolina Christen, Luz María Valarezo, Jaume Bofill, Nela Filimon, and Jaume Armengou. "Decision-making tool for enhancing the sustainable management of cultural institutions: Season content programming at Palau De La Música Catalana." MDPI AG, 2020. http://hdl.handle.net/10757/656665.

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There has been an increasing relevance of the cultural sector in the economic and social development of different countries. However, this sector continues without much input from multi-criteria decision-making (MDCM) techniques and sustainability analysis, which are widely used in other sectors. This paper proposes an MCDM model to assess the sustainability of a musical institution’s program. To define the parameters of the proposed model, qualitative interviews with relevant representatives of Catalan cultural institutions and highly recognized professionals in the sector were performed. The content of the 2015–2016 season of the ‘Palau de la Música Catalana’, a relevant Catalan musical institution located in Barcelona, was used as a case study to empirically test the method. The method allows the calculation of a season value index (SVI), which serves to make more sustainable decisions on musical season programs according to the established criteria. The sensitivity analysis carried out for different scenarios shows the robustness of the method. The research suggests that more complex decision settings, such as MCDM methods that are widely used in other sectors, can be easily applied to the sustainable management of any type of cultural institution. To the best of the authors’ knowledge, this method was never applied to a cultural institution and with real data.<br>Universitat Oberta de Catalunya
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Samstad, Anna. "Värdering av kriterier vid stora investeringar : En jämförelse mellan olika intressenters uppskattningar av kriterier." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-28064.

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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.<br>På vilket sätt uppskattar olika intressenter ett beslut och dess konsekvenser, och hur skiljer sig dessa uppskattningar åt? När företag idag står inför stora beslut behöver de ta hänsyn till aspekter som är både ekonomiska, ekologiska och sociala. För att beslutet ska bli bra behöver de ta hänsyn till samhället och dess olika intressentgrupper. Denna studie är en undersökning av hur olika grupper värderar och viktar olika kriterier. Studien har utförts mot projektet Sundsvall Logistikpark med kriterier relaterade till projektet. Målet med studien har varit att hitta ett sätt att värdera och vikta olika kriterier för att sedan göra en jämförelse av hur företaget och intressenterna uppskattar dessa kriterier. För att göra detta har intervjuer utförts med personer som är extra insatta i projektet med Sundsvall logistikpark och en enkät skickats ut till boende i Sundsvall. Informanterna och respondenterna har fått uppskatta värden och vikter på kriterierna utifrån ett indirekt alternativ där logistikparken inte byggs. Datan har sedan sammanställts genom att använda multiattributsnyttoteori som verktyg för att presentera jämförelsen. Resultatet av undersökningen tyder på att de skillnader som finns i värderingar och viktningar av kriterierna dels beror på en viss osäkerhet angående hur logistikparken skulle kunna påverka de olika kriterierna och hur ett värde kan uppskattas på dessa, men att den största orsaken troligen beror på vilket perspektiv personen ser logistikparken på. Om personen ser på logistikparken från ett industriellt perspektiv blir kriterier som har med industriell utveckling att göra viktigare och tar större plats i analysen. Om personen ser på logistikparken från ett individuellt och socialt perspektiv blir sådana kriterier viktigare och tar större plats i analysen
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Park, Joonam. "Development and Application of Probabilistic Decision Support Framework for Seismic Rehabilitation of Structural Systems." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4898.

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Seismic rehabilitation of structural systems is an effective approach for reducing potential seismic losses such as social and economic losses. However, little or no effort has been made to develop a framework for making decisions on seismic rehabilitation of structural systems that systematically incorporates conflicting multiple criteria and uncertainties inherent in the seismic hazard and in the systems themselves. This study develops a decision support framework for seismic rehabilitation of structural systems incorporating uncertainties inherent in both the system and the seismic hazard, and demonstrates its application with detailed examples. The decision support framework developed utilizes the HAZUS method for a quick and extensive estimation of seismic losses associated with structural systems. The decision support framework allows consideration of multiple decision attributes associated with seismic losses, and multiple alternative seismic rehabilitation schemes represented by the objective performance level. Three multi-criteria decision models (MCDM) that are known to be effective for decision problems under uncertainty are employed and their applicability for decision analyses in seismic rehabilitation is investigated. These models are Equivalent Cost Analysis (ECA), Multi-Attribute Utility Theory (MAUT), and Joint Probability Decision Making (JPDM). Guidelines for selection of a MCDM that is appropriate for a given decision problem are provided to establish a flexible decision support system. The resulting decision support framework is applied to a test bed system that consists of six hospitals located in the Memphis, Tennessee, area to demonstrate its capabilities.
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Books on the topic "Leveraging Multi-Attribute Utility Theory"

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Selecting Remediation Technologies Through A 'Technical Risk' Index. An Application of Multi-Attribute Utility Theory. Storming Media, 1996.

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Book chapters on the topic "Leveraging Multi-Attribute Utility Theory"

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Sarin, Rakesh K. "Multi-attribute utility theory." In Encyclopedia of Operations Research and Management Science. Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_644.

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Mateo, José Ramón San Cristóbal. "Multi-Attribute Utility Theory." In Multi Criteria Analysis in the Renewable Energy Industry. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2346-0_10.

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Sarin, Rakesh K. "Multi-attribute Utility Theory." In Encyclopedia of Operations Research and Management Science. Springer US, 2013. http://dx.doi.org/10.1007/978-1-4419-1153-7_644.

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Malakooti, B. "A Nonlinear Multi-Attribute Utility Theory." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-46536-9_12.

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Garmabaki, A. H. S., Alireza Ahmadi, and Mahdieh Ahmadi. "Maintenance Optimization Using Multi-attribute Utility Theory." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23597-4_2.

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Kabassi, Katerina, and Maria Virvou. "Combination of a Cognitive Theory with the Multi-attribute Utility Theory." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45224-9_126.

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Ferreira, Rodrigo J. P., Adiel T. de Almeida, and Cristiano A. V. Cavalcante. "Selection of Inspection Intervals Based on Multi-attribute Utility Theory." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37140-0_37.

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Maravanyika, Munyaradzi, and Nomusa Dlodlo. "Selecting Attributes for Inclusion in an Educational Recommender System Using the Multi-attribute Utility Theory." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01535-0_18.

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"Multi-attribute utility theory." In Multi-Criteria Decision Analysis. John Wiley & Sons Ltd, 2013. http://dx.doi.org/10.1002/9781118644898.ch4.

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"Structured Trade-Offs for Multiple Objective Decisions: Multi-Attribute Utility Theory." In Value-Added Decision Making for Managers. Chapman and Hall/CRC, 2011. http://dx.doi.org/10.1201/b11458-9.

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Conference papers on the topic "Leveraging Multi-Attribute Utility Theory"

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Sodhi, Ranjana. "Evaluating PMU site performance with multi attribute utility theory." In 2013 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). IEEE, 2013. http://dx.doi.org/10.1109/isgt-asia.2013.6698757.

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Rikki, Alex, Doni El Rezen Purba, and Zekson Arizona Matondang. "Multi attribute utility theory (MAUT) to grant teacher certification eligibility." In SCIENCE AND TECHNOLOGY RESEARCH SYMPOSIUM 2022. AIP Publishing, 2024. http://dx.doi.org/10.1063/5.0224573.

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Chang, Wei-Lun. "Using Multi-attribute Utility Theory to Rank and Select Co-branding Partners." In 2008 Eighth International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2008. http://dx.doi.org/10.1109/isda.2008.220.

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Liu, Ping, Qiming Li, and Xin Wan. "Optimizing a Construction Planning Schedule Based on the Multi-Attribute Utility Theory." In International Conference on Construction and Real Estate Management 2016. American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784480274.050.

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Khalafalla, Mohamed, and Jorge A. Rueda-Benavides. "Value for Money-Based Project Selection Framework Using Multi-Attribute Utility Theory." In Construction Research Congress 2024. American Society of Civil Engineers, 2024. http://dx.doi.org/10.1061/9780784485286.006.

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Pang, Ming-bao, and Xin-ping Zhao. "Coordinative development of regional logistics system by using multi-attribute utility function theory." In 2008 IEEE International Conference on Management of Innovation & Technology (ICMIT 2008). IEEE, 2008. http://dx.doi.org/10.1109/icmit.2008.4654514.

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Liu, Hong-yu, and Ying Li. "Coordinative development of urban traffic and transportation system using multi-attribute utility theory." In 2010 2nd Conference on Environmental Science and Information Application Technology (ESIAT). IEEE, 2010. http://dx.doi.org/10.1109/esiat.2010.5567362.

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Gunawan, Heri, and Hari Ramadhan. "Increased Accuracy of Selection High Performing Employees Using Multi Attribute Utility Theory (MAUT)." In 2018 6th International Conference on Cyber and IT Service Management (CITSM). IEEE, 2018. http://dx.doi.org/10.1109/citsm.2018.8674060.

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Thevenot, Henri J., Elizabeth D. Steva, Gül E. Okudan, and Timothy W. Simpson. "A Multi-Attribute Utility Theory-Based Approach to Product Line Consolidation and Selection." In ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASME, 2006. http://dx.doi.org/10.1115/detc2006-99506.

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Febriandirza, Arafat, Muhammad Rizky Kurniawan, and Arti Dian Nastiti. "Web-Based Decision Support System of Employee Admission Using Multi Attribute Utility Theory." In 2023 International Conference on Computer, Control, Informatics and its Applications (IC3INA). IEEE, 2023. http://dx.doi.org/10.1109/ic3ina60834.2023.10285739.

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Reports on the topic "Leveraging Multi-Attribute Utility Theory"

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Silsdorf, Maria E. Use of Multi-Attribute Utility Theory to Quantify the Desirability of Boiling Water Reactor Hydraulic Control Unit Maintenance Options. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada410662.

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