Proposal of the Integrated Geothermal Centre Model and its Allocation

2014 ◽  
Vol 708 ◽  
pp. 53-58
Author(s):  
Daniela Marasová ◽  
Jana Jablonská ◽  
Miriam Andrejiová ◽  
Slavomír Drevko

The main aim of this article is to propose a model of an integrated geothermal spa resort and its allocation using multi-criteria decision making. Proposal for allocation of mentioned spa resort is defined on the basis of the evaluation criteria.

Author(s):  
Vagif Salimov

The article is devoted to the problem of  software selection. As a rule, this tasks are formalized as models of multi-criteria decision making (MCDM). The peculiarity of this problem is in the fact that the evaluation criteria , is generally defined by linguistic expert. This requires the use of special methods, in particularly, the theory of fuzzy sets. To solve the problem, an approach based on the  a fuzzy measure  was used . In general, a fuzzy measure allows one to take into account the effect of the mutual influence of criteria. The main difficulty lies in identifying this measure. The fuzzy Sugeno measure and  Sugeno integral were used. An example of solving the indicated problem is given.


2013 ◽  
Vol 14 (5) ◽  
pp. 957-978 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini ◽  
Mohammad Majid Fouladgar ◽  
Edmundas Kazimieras Zavadskas ◽  
S. Hamzeh Haji Moini

Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives.


Author(s):  
A. O. Matin ◽  
F. Misagh

The aim of this research is to evaluate the proposed bids using impartial and entropy weights in a multi-criteria decision-making model. We use matrix data for hypothetical bidding involving nine criteria, with the presence of four domestic and two foreign contractors. Then, using cumulative entropy function, we estimate the entropy weights and use it in a multi-criteria decision-making model. The criteria of experience and knowledge in the field, good history and satisfaction in previous projects, financial and support capabilities, localization of the contractor, having the experience at the site of the project, availability and readiness of equipment and machines, the adequacy of technical staff, the work quality system, the efficient management and appropriate management system, creativity and innovation in similar tasks are the input variables of the decision model. After analyzing them, the proposals are prioritized through a multi-criteria decision-making model. The research findings include Shannon entropy and cumulative entropy-based weights for evaluation criteria and after applying the specific weight for the proposed quotation, the utility rate of each contractor is calculated. The results showed that the use of modified multi-dimensional decision-making method is more advantageous than traditional methods of evaluating bidding proposals in selecting the winner of a tender, and also using cumulative entropy weights in comparison with Shannon's leads to a more realistic choice of contractors.


2020 ◽  
Vol 18 (3) ◽  
pp. 357 ◽  
Author(s):  
Yousaf Ali ◽  
Bilal Mehmood ◽  
Muhammad Huzaifa ◽  
Umair Yasir ◽  
Amin Ullah Khan

Increasing competition in the automobile industry has led to a vast variety of choices when buying a car thus making car selection a tedious task. The objective of this research is to develop a new hybrid multi-criteria decision-making technique, with accuracy greater than that of the already existing methods, in order to help the people in decision-making while buying a car. Hence, considering a broader spectrum, this study aims at easing the process of multi-criteria decision-making problems in different fields. To achieve the objective, seven different alternatives were evaluated with respect to the enlisted evaluation criteria, which were selected after analyzing the secondary data obtained from Pak wheels based on style, fuel economy, price, comfort and performance. These criteria were then analyzed using the proposed Full Consistency Fuzzy TOPSIS method. As the name tells, this method is a unique combination of two techniques. The Full Consistency method is used to calculate the weights of the criteria while the Fuzzy TOPSIS approach is applied to rank the alternatives according to their scores in the selected criteria. The outcomes demonstrate an increase in the consistency ratio of the weight coefficients due to which the ranking of the alternatives by the FCF-TOPSIS is more accurate than the TOPSIS and the Analytical Hierarchy Process. The novelty of the method lies in the fact that this combination has not been used for an alternative selection scenario before. In addition to this, it can be used in various industries where a choice between the available alternatives arises based on a set of evaluation criteria.


2019 ◽  
Vol 11 (6) ◽  
pp. 1506 ◽  
Author(s):  
Chia-Chen Yang ◽  
Shang-Ling Ou ◽  
Li-Chang Hsu

Along with economic development and social progress, environmental issues are increasingly becoming the subject of public concern. Through green credit, banks intentionally direct money into resource-conserving technology development and environmental protection industries, thus, encouraging enterprises to focus on green products. Therefore, establishing a reasonable green credit evaluation mechanism for banks is an important issue. Based on this, this study combines grey relational analysis (GRA), the Decision-Making Trial and Evaluation Laboratory technique (DEMATEL), analytic network process (ANP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to develop a hybrid multi-criteria decision-making (MCDM) model for quantifying data and, thereby, to establish a green credit rating mechanism. In order to verify the model, this study combines credit risk and economic, environmental and social performance evaluation criteria as green credit evaluation criteria. There are 55 high-tech listed companies in Taiwan in 2014 taken as the evaluation objects and conducted for a performance ranking. The empirical results can serve as a reference for financial authorities promoting green finance policies and for investors making investment decisions.


2020 ◽  
Vol 8 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Ilham Huseyinov ◽  
Feride Savaroglu Tabak

The main purpose of this study is to present a systematic methodology based on fuzzy Multi-Criteria Decision-Making (FMCDM) models to help users evaluate computer algebra systems (CAS). CAS is a software package for the manipulation of mathematical formulas. The suggested methodology is user-centred which involves users' subjective evaluation judgments. User judgments are represented by means of fuzzy linguistic modelling techniques. An evaluation criteria framework based on the concept of the usefulness of CAS is developed. Next, two FMCDM models – fuzzy Analytical Hierarchy Process (FAHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) are proposed for the evaluation procedure. The FAHP is applied to determine the relative importance weights of qualitative evaluation criteria; the FTOPSIS is applied to rank the CAS alternatives. The illustrated case study demonstrates the applicability and effectiveness of the proposed methodology.


2012 ◽  
Vol 18 (3) ◽  
pp. 529-543 ◽  
Author(s):  
Sarfaraz Hashemkhani Zolfani ◽  
I-Shuo Chen ◽  
Nahid Rezaeiniya ◽  
Jolanta Tamošaitienė

This paper is aimed at utilizing a hybrid multi-criteria decision making (MCDM) model for selecting a supplier. First, eight evaluation criteria, including cost, quality, distance, delivery reliability, reputation, technology level, compatibility and development ability are identified. The A nalytic H ierarchical P rocess (AHP) is initially used for calculating the weight of each criterion. The CO mplex PR oportional AS sessment of alternatives to G rey relations (COPRAS-G method) is adopted for ranking and selecting suppliers. In order to illustrate the functional ability of the developed model, Kalleh Company is chosen as a case study and can be used as a pattern for supplier selection and future researches.


2020 ◽  
Vol 26 (3) ◽  
pp. 573-598 ◽  
Author(s):  
Juan-juan Peng ◽  
Chao Tian ◽  
Wen-yu Zhang ◽  
Shuai Zhang ◽  
Jian-qiang Wang

Sustainable supplier selection (SSS) is an important part of sustainable supply chain management (SSCM). In this paper, an integrated multi-criteria decision-making (MCDM) framework, based on the picture fuzzy exponential entropy, and the VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method, is proposed to manage SSS problems. Firstly, the evaluation criteria of SSS, including economic, environmental and social, is established. This can be evaluated in the form of the actual data or linguistic terms provided by suppliers and experts respectively in an actual decision-making process. Then, according to the translated scales, all the evaluation information can be converted into picture fuzzy numbers (PFNs). Secondly, the picture fuzzy exponential entropy is defined. Moreover, based on the entropy’s minimization principle, the defined picture fuzzy exponential entropy is used to determine the weight of the SSS’s criteria. Thirdly, the extended VIKOR method, which combines the grey correlation coefficient, is utilized to select a suitable supplier. This method avoids the shortcomings of the traditional VIKOR method in data mining and solves the conflict between SSS criteria. Finally, the feasibility and effectiveness of the proposed integrated decision framework are verified by an experiment, as well as a sensitivity analysis and comparative analysis.


Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3136
Author(s):  
Pham Ngoc Toan ◽  
Thanh-Tuan Dang ◽  
Le Thi Thu Hong

Education has changed dramatically due to the severe global pandemic COVID-19, with the phenomenal growth of e-learning, whereby teaching is undertaken remotely and on digital platforms. E-learning is revolutionizing education systems, as it remains the only option during the ongoing crisis and has tremendous potential to fulfill instructional plans and safeguard students’ learning rights. The selection of e-learning platforms is a multi-criteria decision-making (MCDM) problem. Expert analyses over numerous criteria and alternatives are usually linguistic terms, which can be represented through grey numbers. This article proposes an integrated approach of grey analytic hierarchy process (G-AHP) and grey technique for order preference by similarity to ideal solution (G-TOPSIS) to evaluate the best e-learning website for network teaching. This introduced approach handles the linguistic evaluation of experts based on grey systems theory, estimates the relative importance of evaluation criteria with the G-AHP method, and acquires e-learning websites’ ranking utilizing G-TOPSIS. The applicability and superiority of the presented method are illustrated through a practical e-learning website selection case in Vietnam. From G-AHP analysis, educational level, price, right and understandable content, complete content, and up-to-date were found as the most impactful criteria. From G-TOPSIS, Edumall is the best platform. Comparisons are conducted with other MCDM methods; the priority orders of the best websites are similar, indicating the robust proposed methodology. The proposed integrated model in this study supports the stakeholders in selecting the most effective e-learning environments and could be a reference for further development of e-learning teaching-learning systems.


Author(s):  
Tom Wanyama ◽  
◽  
Behrouz Homayoun Far

In Multi-Criteria Decision Making problems such as choosing a development policy, selecting software products, or searching for commodities to purchase, it is often necessary to evaluate solution options in respect of multiple objectives. The solution alternative that performs best in all the objectives is the dominant solution, and it should be selected to solve the problem. However, usually the selection objectives are incomparable and conflicting, making it impossible to have a dominant solution among the alternatives. In such cases, tradeoff analysis is required to identify the objectives that can be optimized, and those that can be comprised in order to choose a winning solution. In this paper we present a tradeoff analysis model based on the principles of qualitative reasoning that provides visualization support for understanding interaction and tradeoff dependences among solutions evaluation criteria which affect the tradeoff among selection objectives. Moreover, the decision support system based on our tradeoff analysis model facilitates discovery of hidden solution features so as improve the completeness and certainty of the user preference model.


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