18,275 research outputs found

    A fuzzy hierarchical multiple criteria group decision support system - Decider - and its applications

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    Decider is a Fuzzy Hierarchical Multiple Criteria Group Decision Support System (FHMC-GDSS) designed for dealing with subjective, in particular linguistic, information and objective information simultaneously to support group decision making particularly on evaluation. In this chapter, the fuzzy aggregation decision model, functions and structure of Decider are introduced. The ideas to resolve decision and evaluation problems we have faced in the development and application of Decider are presented. Two real applications of the Decider system are briefly illustrated. Finally, we discuss our further research in this area. © 2011 Springer-Verlag Berlin Heidelberg

    An intelligent group decision-support system and its application for project performance evaluation

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    Purpose: In any organization there are main goals, with lots of projects designed to achieve these goals. It is important for any organization to determine how much these projects affect the achievement of these goals. The purpose of this paper is to develop a fuzzy multiple attribute-based group decision-support system (FMAGDSS) to evaluate projects' performance in promoting the organization's goals utilizing simple additive weighting (SAW) algorithm and technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. The proposed FMAGDSS deals with choosing the most appropriate fuzzy ranking algorithm for solving a given fuzzy multi attribute decision making (FMADM) problem with both qualitative and quantitative criteria (attributes), and uncertain judgments of decision makers. Design/methodology/approach: In this paper, a FMAGDSS model is designed to determine scores and ranks of every project in promoting the organization's goals. In the first step of FMAGDSS model, all projects are assessed by experts based on evaluation criteria and the organization's goals. The proposed FMAGDSS model will then choose the most appropriate fuzzy ranking method to solve the given FMADM problem. Finally, a sensitivity analysis system is developed to assess the reliability of the decision-making process and provide an opportunity to analyze the impacts of "criteria weights" and "projects" performance' on evaluating projects in achieving the organizations' goals, and to assess the reliability of the decision-making process. In addition, a software prototype has been developed on the basis of FMAGDSS model that can be applied to solve every FMADM problem that needs to rank alternatives according to certain attributes. Findings: The result of this study simplifies and accelerates the evaluation process. The proposed system not only helps organizations to choose the most efficient projects for sustainable development, but also helps them to assess the reliability of the decision-making process, and decrease the uncertainty in final decision caused by uncertain judgment of decision makers. Research limitations/implications: Future studies are suggested to expand this system to evaluate and rank the project proposals. To achieve this goal, the efficiency of the projects in line with organization's goals, should be predicted.Originality/value: This study contributes to the relevant literature by proposing a FMAGDSS model to evaluate projects in promoting organization's goals. The proposed FMAGDSS has ability to choose the most appropriate fuzzy ranking algorithm to solve a given FMADM problem based on the type and the number of attributes and alternatives, considering the least computation and time consumption for ranking alternatives. © Emerald Group Publishing Limited

    Reverse logistics applied to E-commerce: A Systematic Literature Review on Methods, Applications, and Trends for a Virtual Sustainable Market / Logística reversa aplicada ao comércio eletrônico: uma revisão sistemática da literatura sobre métodos, aplicações e tendências para um mercado virtual sustentável

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    The digital transformation of society, strengthened by the social isolation resulting from the COVID-19 pandemic, boosted sales and returns of products in e-commerce. In this sense, reverse logistics in e-commerce (RLec) has become essential to meet environmental legislation and consumer expectations, which evaluate exchange policies on new purchases. In this sense, this article presents a systematic review of the literature and content analysis, from 2009 to 2019, to identify methods of decision making and applications in RLec. Thus, 261 publications were selected, of which 92 met the search criteria related to reverse logistics and only 7 applied to e-commerce. In view of this, the main applications involved network design (26%), remanufacturing (21%) and outsourcing (16%), aiming at reducing costs and identifying barriers in reverse operations. Finally, artificial intelligence for decision making was identified as a competitive differential in reducing the complexity and subjectivity of LRec problems

    Learning Content and Software Evaluation and Personalisation Problems

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    The paper aims to analyse several scientific approaches how to evaluate, implement or choose learning content and software suitable for personalised users/learners needs. Learning objects metadata customisation method as well as the Method of multiple criteria evaluation and optimisation of learning software represented by the experts' additive utility function are analysed in more detail. The value of the experts' additive utility function depends on the learning software quality evaluation criteria, their ratings and weights. The Method is based on the software engineering Principle which claims that one should evaluate the learning software using the two different groups of quality evaluation criteria - `internal quality' criteria defining the general software quality aspects, and `quality in use' criteria defining software personalisation possibilities. The application of the Method and Principle for the evaluation and optimisation of learning software is innovative in technology enhanced learning theory and practice. Application of the method of the experts' (decision makers') subjectivity minimisation analysed in the paper is also a new aspect in technology enhanced learning science. All aforementioned approaches propose an efficient practical instrumentality how to evaluate, design or choose learning content and software suitable for personalised learners needs

    Influence of Portfolio Management in Decision-Making

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    Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem has been addressed to enable on-time completion of customer orders in a lean manufacturing environment. The problem is optimizing the partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components. Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid excess final product inventory. The first model is a non-linear integer programming model whereas the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented. Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times compared to the other two models. It has also been showed that the alternative model is able to solve moderate sized real-world problems. Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature owing to the inclusion of new circumstances that are present in real-world applications. Those are: customer orders consisting of multi-products made of multi-parts, processing of all parts of the same product from different orders in the same batch, and delivering the orders only when all related products are completed. This research also contributes to the literature of batch scheduling problem by presenting new optimization models.Peer Reviewe

    Measuring the Quality of Financial Electronic Payment System: Combined with Fuzzy AHP and Fuzzy TOPSIS

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    The study aims to apply Fuzzy AHP in TOPSIS to discuss the key factors that foster the success of current third-party online payment platforms. This study organized the quality measurements into four categories and eleven sub-categories. The AHP in TOPSIS is applied to calculate the weighted averages of all categories and sub-categories to measure the quality of third-party online payment platforms. This study finds that “safety quality” is the most emphasized category, “system quality” is the second, “communication quality” is the third, and “service quality” is the least emphasized

    An integrated multi-criteria decision-making framework for a medical device selection in the healthcare industry

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    Medical devices used in healthcare organizations are costly, and the process of selecting these devices requires considering multiple criteria such as effectiveness and ease of use. Careful selection of these devices is daunting since it entails the evaluation of various measures. This research investigates the selection process of the same type of medical devices, especially when alternatives are available, and the organization needs to make a good selection. A Multi-Criteria Decision-Making (MCDM) framework based on the integration of the Analytical Hierarchy Process (AHP) and ELimination Et Choice Translating Reality (ELECTRE) method is developed. The framework model includes 10 criteria, which are selected based on real-life inputs from professional physicians. Seven Ultrasound machines (referred to as alternatives) are evaluated using the developed framework. A case study is conducted on the best selection practice of an Ultrasound machine in a gynecology clinic based in the Kingdom of Jordan. Results revealed that the best and worst alternatives of ultrasound machines are identified and compared with all other options

    Guidance on the integrated assessment of complex health technologies: the INTEGRATE-HTA model

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    Challenges in assessments of health technologies In recent years there have been major advances in the development of health technology assessment (HTA). However, HTA still has certain limitations when assessing technologies which are complex, i.e. consist of several interacting components, target different groups or organizational levels, have multiple and variable outcomes, and/or permit a certain degree of flexibility or tailoring (Craig et al., 2008), fi are context-dependent - current HTA usually focusses on the technology, not on the system within which it is used, fi perform differently depending on the way they are implemented, fi have different effects on different individuals. Furthermore, HTA usually assesses and appraises aspects side-by-side, while decision-making needs an integrated perspective on the value of a technology. In the EU-funded INTEGRATE-HTA project, we developed concepts and methods to deal with these challenges, which are described in six guidances. Because of the interactions, an integrated assessment needs to start from the beginning of the assessment. This guidance provides a systematic five-step-process for an integrated assessment of complex technologies (the INTEGRATE-HTA Model). Purpose and scope of the guidance The aim of the INTEGRATE-HTA project is to provide concepts and methods that enable a patient-centred, comprehensive, and integrated assessment of complex health technologies. The purpose of this guidance is to structure the overall HTA-process. The INTEGRATE-HTA Model outlines an integrated scoping process, a coordinated application of assessment methods for different aspects and an integrated and structured decision-making process. It is intended for HTA agencies, HTA researchers and those engaged in the evaluation of complex health technologies. As it links the assessment to the decision-making process, it also addresses HTA commissioners and other stakeholders using or planning HTAs. While all technologies are arguably complex, some are more complex than others. Applying this guidance might lead to a more thorough and therefore more time-consuming process. Depending on the degree of complexity, one might choose to follow the whole process as described in this guidance, or only focus on certain steps. The guidance provides an operational definition to assess the complexity of technologies which can be used to identify specific aspects that will need more attention than others. What the guidance does not provide is a post-hoc solution for assessments that have already been completed. | 6 Development of the guidance The INTEGRATE-HTA Model presented in this guidance was developed based on a systematic literature search on approaches for integration, on the experiences of traditional HTAs, as well as on the other methodological guidances developed in the INTEGRATE-HTA project. It was tested in a case study on palliative care and iteratively revised during the practical application. The guidance was again revised after internal and external peer-review. Application of this guidance For a comprehensive integrated assessment of a complex technology, we developed a five-step process, the INTEGRATE-HTA model. In Step 1, the HTA objective and the technology are defined with the support from a panel of stakeholders. An initial logic model is developed in Step 2. The initial logic model provides a structured overview of the technology, the context, implementation issues, and relevant patient groups. It then frames the assessment of the effectiveness, as well as economic, ethical, legal, and socio-cultural aspects in Step 3. In Step 4, a graphical overview of the assessment results, structured by the logic model, is provided. Step 5 is a structured decision-making process informed by the HTA (and is thus not formally part of the HTA, but follows it). fi Step 1: In step 1, the technology under assessment and the objective of the HTA are defined. Especially for complex technologies, such as palliative care, the definition of the technology alone is a challenge that must not be underestimated. It is recommended to do this based on a tentative literature review and with the support of stakeholder advisory panels (SAPs) which should comprise clinical experts, academics, patients, possibly their relatives and/or other caretakers, and the public. The setting of an objective considering all relevant aspects of complexity and structured by assessment criteria is important. The assessment criteria will usually reflect values of the stakeholders as well as the input from the theoretical, methodological and empirical literature. fi Step 2: In step 2, an initial logic model is developed (see Guidance on the use of logic models in health technology assessments of complex interventions). The model provides a structured overview on participants, interventions, comparators, and outcomes. Parallel to this, groups of patients that are distinguished by different preferences and treatment moderators (see Guidance for the assessment of treatment moderation and patients’ preferences) are identified. Specific context and implementation issues are also identified as part of the initial logic model (see Guidance for the Assessment of Context and Implementation in Health Technology Assessments (HTA) and Systematic Reviews of Complex Interventions). The product of this step is the logic model as a graphical representation of all aspects and their interactions that are relevant for the assessment of the complex technology. fi Step 3: In step 3, the logic model serves as a conceptual framework that guides the evidence assessment. Depending on the specific aspect (e.g. effectiveness, economic, ethical, socio-cultural, or legal aspects) different methods are available for the assessment (see Guidance for assessing effectiveness, economic aspects, ethical aspects, socio-cultural aspects and legal aspects in complex technologies). The outputs of step 3 are evidence reports and standardized evidence summaries for each assessment aspect (e.g. report on economics, report on ethical aspects, etc.). fi Step 4: In step 4, the assessment results of step 3 are structured using the logic model developed in step 2. Whereas the initial logic model in step 2 specifies what evidence is relevant, the extended logic model to assist decision-making in step 4 visualizes the assessment results as well as the interaction with respect to the HTA objectives. It also allows for the consideration of different scenarios depending on the variation in context, implementation and patient characteristics. 7 | fi Step 5: Step 5 involves a structured decision-making process and is not an integral part of the HTA in the narrow sense. Decision-making can be supported by applying quantitative e.g. MCDA- (Multi-criteria decision analysis) or qualitative decision support tools. Flexibility in the application of these tools by the decision committee is crucial, taking different decision settings and evidence needs into consideration. Conclusions In current HTA, different aspects are usually assessed and presented independent of each other. Context, implementation issues and patient characteristics are rarely considered. The INTEGRATE-HTA Model enables a coordinated assessment of all these aspects and addresses their interdependencies. The perspective of stakeholders such as patients and professionals with their values and preferences is integrated in the INTEGRATE-HTA Model to obtain HTA results that are meaningful for all relevant stakeholders. Finally, health policy makers obtain an integrated perspective of the assessment results to achieve fair and legitimate conclusions at the end of the HTA process. The application of the model will usually require more time and resources than traditional HTA. An initial assessment of the degree and the character of complexity of a technology might be helpful to decide whether or not the whole process or only specific elements will be applied
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