A process model for group decision making with quality evaluation

Série : Lecture Notes in Computer Science, vol. 5518In this work it is addressed the problem of information evaluation and decision making process in Group Decision Support Systems (GDSS). A Multi-valued Extended Logic Programming language is used for imperfect information representation and reasoning. A model embodying the quality evaluation of the information, along the several stages of the decision making process, is presented. This way we give the decision makers a measure of the value of the information that supports the decision itself. This model is presented in the context of a GDSS for VirtualECare, a system aimed at sustaining online healthcare services. Reasoning with incomplete and uncertain knowledge has to be dealt with in this kind of environment, due to the particular nature of the healthcare services, where the awful consequences of bad decisions, or lack of timely ones, demand for a responsible answer

Power distribution system planning evaluation by a fuzzy multi-criteria group decision support system

The evaluation of solutions is an important phase in power distribution system planning (PDSP) which allows issues such as quality of supply, cost, social service and environmental implications to be considered and usually involves the judgments of a group of experts. The planning problem is thus suitable for the multi-criteria group decision-making (MCGDM) method. The evaluation process and evaluation criteria often involve uncertainties incorporated in quantitative analysis with crisp values and qualitative judgments with linguistic terms; therefore, fuzzy sets techniques are applied in this study. This paper proposes a fuzzy multi-criteria group decision-making (FMCGDM) method for PDSP evaluation and applies a fuzzy multi-criteria group decision support system (FMCGDSS) to support the evaluation task. We introduce a PDSP evaluation model, which has evaluation criteria within three levels, based on the characteristics of a power distribution system. A case-based example is performed on a test distribution network and demonstrates how all the problems in a PDSP evaluation are addressed using FMCGDSS. The results are acceptable to expert evaluators. © 2010 Taylor & Francis Group, LLC

A model-based methodology for the evaluation of computerized group decision making

Increased global competition is forcing organizations to increase their use of group decision making today. Computerized group decision support aids (CGDSAs) are being developed to improve the efficiency of these groups and to improve decision quality. Even though the use of CGDSAs has increased, very little research has been done on the evaluation of CGDSAs. The purpose of this research was to develop a model-based generalized methodology for CGDSA evaluation from the user's perspective. Two models were developed as a foundation for the CGDSA evaluation methodology. The first model was a model of group decision making and the second model was a model of computer-aided group decision making. The group decision making model was based upon a basic input-output model with the problem as the input and the selected alternative as the output. Analogous to how problems are viewed in terms of classical design of experiments, independent variables affect the outcome (problem solution the dependent variable) of the decision making process. As in design of experiments, independent variables are either noise variables or control variables. In the model presented, the independent variables are further divided into four categories (internal, external, process, and problem) in the group decision making model as a way to help develop an exhaustive list of independent variables affecting the decision making process. The generalized methodology for CGDSA evaluation mapped directly to the computer-aided group decision making model. Solution quality is measured directly or by measuring independent variables that have been previously been correlated to solution quality using standard design of experiment techniques. The generalized methodology for CGDSA evaluation was applied to the assessment of ConsensusBuilder, an example of a CGDSA. As prescribed by the CGDSA evaluation methodology, usability was also assessed and practical use considerations were followed when designing the evaluation. The value of the ConsensusBuilder evaluation for this research was that it was possible to perform a thorough evaluation of ConsensusBuilder, a CGDSA, using the CGDSA Evaluation Methodology developed in this research. In addition to the ConsensusBuilder evaluation, six different CGDSA evaluations cited in the literature were assessed in terms of the CGDSA evaluation methodology

Granular computing and optimization model-based method for large-scale group decision-making and its application

In large-scale group decision-making process, some decision makers hesitate among several linguistic terms and cannot compare some alternatives, so they often express evaluation information with incomplete hesitant fuzzy linguistic preference relations. How to obtain suitable large-scale group decision-making results from incomplete preference information is an important and interesting issue to concern about. After analyzing the existing researches, we find that: i) the premise that complete preference relation is perfectly consistent is too strict, ii) deleting all incomplete linguistic preference relations that cannot be fully completed will lose valid assessment information, iii) semantics given by decision makers are greatly possible to be changed during the consistency improving process. In order to solve these issues, this work proposes a novel method based on Granular computing and optimization model for large-scale group decision-making, considering the original consistency of incomplete hesitant fuzzy linguistic preference relation and improving its consistency without changing semantics during the completion process. An illustrative example and simulation experiments demonstrate the rationality and advantages of the proposed method: i) semantics are not changed during the consistency improving process, ii) completion process does not significantly alter the inherent quality of information, iii) complete preference relations are globally consistent, iv) final large-scale group decision-making result is acquired by fusing complete preference relations with different weights

PEMILIHAN ENGINEERING CONTRACTOR PROYEK DANA HIBAH ENERGI TERBARUKAN DENGAN METODE DEMATEL DAN ANP

One of the success keys of the grant fund program for the renewable energy project is in the decision making process to find the engineering contractor with the best quality, effectiveness, and efficiency to implement the process of procurement of goods and services. The objective of this research is to design a systematic selection model for the engineering contractor referring to the conditions, situations, and scopes as required by the "Y" institution. Data were processed using Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analityc Network Process (ANP). The decision criteria referred to the PEPRES No. 70/2012, PERMEN No. 08/PRT/M/2011, and the results of Focus Group Discussion (FGD) conducted by the evaluation team. The assesments from the evaluation team were including internal and financial capability, technical capability, organizational capability, commitment to quality assurance, commitment to health and safety, and pricing. Keywords:     Selection of Engineering Contractor, Grant Fund, Renewable Energy, Decision Making Trial and Evaluation, Analytic Network Process

Evaluator-blinded trial evaluating nurse-led immunotherapy DEcision Coaching In persons with relapsing-remitting Multiple Sclerosis (DECIMS) and accompanying process evaluation: Study protocol for a cluster randomised controlled trial

License:Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)Background: Multiple sclerosis is a chronic neurological condition usually starting in early adulthood and regularly leading to severe disability. Immunotherapy options are growing in number and complexity, while costs of treatments are high and adherence rates remain low. Therefore, treatment decision-making has become more complex for patients. Structured decision coaching, based on the principles of evidence-based patient information and shared decision-making, has the potential to facilitate participation of individuals in the decision-making process. This cluster randomised controlled trial follows the assumption that decision coaching by trained nurses, using evidence-based patient information and preference elicitation, will facilitate informed choices and induce higher decision quality, as well as better decisional adherence. Methods/Design: The decision coaching programme will be evaluated through an evaluator-blinded superiority cluster randomised controlled trial, including 300 patients with suspected or definite relapsing-remitting multiple sclerosis, facing an immunotherapy decision. The clusters are 12 multiple sclerosis outpatient clinics in Germany. Further, the trial will be accompanied by a mixed-methods process evaluation and a cost-effectiveness study. Nurses in the intervention group will be trained in shared decision-making, coaching, and evidence-based patient information principles. Patients who meet the inclusion criteria will receive decision coaching (intervention group) with up to three face-to-face coaching sessions with a trained nurse (decision coach) or counselling as usual (control group). Patients in both groups will be given access to an evidence-based online information tool. The primary outcome is ‘informed choice’ after six months, assessed with the multi-dimensional measure of informed choice including the sub-dimensions risk knowledge (questionnaire), attitude concerning immunotherapy (questionnaire), and immunotherapy uptake (telephone survey). Secondary outcomes include decisional conflict, adherence to immunotherapy decisions, autonomy preference, planned behaviour, coping self-efficacy, and perceived involvement in coaching and decisional encounters. Safety outcomes are comprised of anxiety and depression and disease-specific quality of life. Discussion: This trial will assess the effectiveness of a new model of patient decision support concerning MS-immunotherapy options. The delegation of treatment information provision from physicians to trained nurses bears the potential to change current doctor-focused practice in Germany

A Novel Hybrid MCDM Approach for Complicated Supply Chain Management Problems in Construction

The paper tackles a hybrid multi-criteria decision-making (MCDM) model related to supply chain management, problems, and the supplier selection problem. Modern management of materials and products requires continuous evaluation of numerous complex social, ecological, and economic factors. A group decision process using Analytic Hierarchical Process (AHP) approach presented to find the criteria weights. Measurement of conflict among criteria and decision makers presented with illustration and numerical example. Firstly, eight evaluation criteria, including cost, quality, distance, and delivery, reliability, reputation, and technology level, compatibility, and development ability identified. Later, the ARAS and the Multiplicative Utility function adopted for ranking and selecting suppliers. Criteria values normalized according to Hovanov method. The ARAS method with this normalisation method named as a hybrid original model INMUARAS.12th international conference “Modern Building Materials, Structures and Techniques” (MBMST 2016

Decision-making in fuzzy environment

Decision-making is a logical human judgment process for identifying and choosing alternatives based on the values and preferences of the decision maker that mostly applied in the managerial level of the concerned department of the organization/ supply chain. Recently, decision-making has gained immense popularity in industries because of their global competitiveness and to survive successfully in respective marketplace.Therefore, decision-making plays a vital role especially in purchase department for reducing material costs, minimizing production time as well as improving the quality of product or service. But, in today’s real life problems, decision-makers generally face lot of confusions, ambiguity due to the involvement of uncertainty and subjectivity in complex evaluating criterions of alternatives. To deal such kind of vagueness in human thought the title ‘Decision-Making in Fuzzy Environment’ has focused into the emerging area of research associated with decision sciences. Multiple and conflicting objectives such as ‘minimize cost’ and ‘maximize quality of service’ are the real stuff of the decision-makers’ daily concerns. Keeping this in mind, this thesis introduces innovative decision aid methodologies for an evaluation cum selection policy analysis, based on theory of multi criteria decision-making tools and fuzzy set theory. In the supplier selection policy, emphasis is placed on compromise solution towards the selection of best supplier among a set of alternative candidate suppliers. The nature of supplier selection process is a complex multi-attribute group decision making (MAGDM) problem which deals with both quantitative and qualitative factors may be conflicting in nature as well as contain incomplete and uncertain information. Therefore, an application of VIKOR method combined with fuzzy logic has been reported as an efficient approach to support decision-making in supplier selection problems. This dissertation also proposes an integrated model for industrial robot selection considering both objective and subjective criteria’s. The concept of Interval-Valued Fuzzy Numbers (IVFNs) combined with VIKOR method has been adapted in this analysis

Comparison of decision-making approaches to prioritization of clean air action plans for sustainable development

Background: Clean air action plans have been prepared and are still being implemented in Turkey to control and prevent air pollution, and improve the air quality. The plans reveal a picture of the current situation and available inventory information. However, in order to implement the identified plans in real life, they need to be prioritized. This study aimed to identify and prioritize clean air action plans for Turkey using a framework of both fuzzy and crisp evaluations. Methods: In this study, priorities of the plans were identified and analyzed with a decision-making model. A three-step research methodology was provided. First, literature was reviewed regarding sustainable development and action plans. Second, in order to narrow and specify action plans, the nominal group technique (NGT) was implemented. Finally, fuzzy analytic hierarchy process (AHP) and best-worst method (BWM) surveys were applied to environmental engineers and experts working on sustainable development to prioritize the action plans. Results: It was revealed that heating dimension is considered as the most important criterion with the weight of 0.7469 in fuzzy AHP and 0.758 in BWM. AP1 with a weight of 0.3356 in fuzzy AHP and AP3 with a weight of 0.3289 in BWM were the most important sub-criteria, which are the plans for reducing coal use ranked at the forefront in reducing air pollution. Conclusion: According to the results, there is no significant difference in the priority ranking results. The results of fuzzy AHP and BWM are very similar. For example, traffic criterion has the best performance in both methods in the evaluation of decision makers. In addition, the main and sub-criteria with the lowest priority are the same in these two methods. Keywords: Air pollution, Cities, Decision making, Surveys and questionnaire