A novel neutrosophic CODAS method: Selection among wind energy plant locations

Sustainability prioritization of technologies for cleaning up soils polluted with oil and petroleum products: A decision support system under complex spherical fuzzy environment

The transition towards a sustainable land management (SLM) needs for utilizing appropriate technologies for controlling soil pollution, and ensures the development of environmental, economic, technical, and social dimensions in region. Using these technologies for cleaning up soils polluted with oil and petroleum products in Behbahan city (in the southwest of Iran) is considered. The soil pollution control technologies (SPCTs) can assist local authorities, governments, investors, and developers to reduce climate change, mitigate soil, water, and air pollution and construct the sustainable communities. With the aim of balance between the issues in the context of sustainability policy, criteria (principles) including environmental, economic, technical, and social aspects are considered. The research takes into consideration the applicability of a novel multi-criteria decision-making approach namely complex spherical fuzzy set-based CODAS (Combinative distance-based assessment). The approach can be used to choose the suitable technology in a sustainable mode, considering the principles related to sustainability pillars. It comprises various technologies for soil pollution control and prioritizes technologies from the most to least as: Biorestoration technology, Excavation technology, Soil venting technology, Soil flushing, and Hydraulic barriers technology.

ERP selection using picture fuzzy CODAS method

The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human’s judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture fuzzy uncertainty based on Euclidean and Taxicab distances and negative ideal solution. ERP system selection problem is handled as the application area of the developed method, picture fuzzy CODAS. Results indicate that the new proposed method finds meaningful rankings through picture fuzzy sets. Comparative analyzes show that the presented method gives successful and robust results for the solutions of MCDM problems under fuzziness.

Assessment Urban Transport Service and Pythagorean Fuzzy Sets CODAS Method: A Case of Study of Ciudad Juárez

The purpose of this research article is to provide a comprehensive method of evaluation for public transportation. In this sense, this study considers transport lines that offer in Ciudad Juárez, Chihuahua. Hence, this study presents a description of the public transport system as part of the literature review. Likewise, the document describes an appropriate model based on the more outstanding publications about urban mobility and public transportation for passengers. Nevertheless, it is based on the Pythagorean Fuzzy combinative distance-based assessment (CODAS) to analyze and evaluate the alternatives through criteria that define general performance. Thus, the integration of these methods provides an adequate methodology for decision-making concerning urban planning and mobility to detect and improve the performance of criteria not considered within sustainable urban mobility plans. Results show how the applied approach can work as a powerful tool for the appraisal of the transport service. Finally, the results give relevant information to the local authority of the transport management of Ciudad Juarez to do improvements focused on the user.

Fuzzy Complex Proportional Assessment Applied in Location Selection for Installation of Photovoltaic Plants

This article proposes the application of a multi-criteria decision-making method based on fuzzy complex proportional assessment (COPRAS-F), applying business sustainability criteria, to rank alternative sites for the installation of photovoltaic plants, as selected from a geographic suitability index map of vast and heterogeneous regions in Southern Brazil, obtained from a geographic information system. As a key feature, the methodology serves the interests of stakeholders during decision-making meetings in a personalized manner, eliminating the need for consensus to overcome conflicts and antagonistic positions, allowing them to maintain a strictly professional view and to communicate in business language. The results indicate that the best location from a geographical viewpoint may not be the best location from a business viewpoint.

Evaluation of smart health technologies with hesitant fuzzy linguistic MCDM methods

Smart health applications are raising a growing interest around the world thanks to its potential to act proactively and solve health related problems with smart technologies. Smart health technologies can provide effective healthcare services such as personalization of treatments through big data, robotics in cure and care, artificial intelligence support to doctors, etc. The mixed structure of the evaluation of smart health technologies involves various contradictory criteria. However, when information is of uncertain nature, it is difficult to decide on how to treat. A hesitant fuzzy linguistic term set (HFLTS) approach is applied to overcome such uncertainties related to this multi-criteria decision-making (MCDM) problem. This approach can be used to facilitate experts’ decision-making processes in complex and uncertain situations. In this study, an integrated hesitant fuzzy linguistic (HFL) MCDM approach is proposed to evaluate smart health technologies. The criteria are weighted with HFL Analytic Hierarchy Process (AHP), and then, smart health technologies are evaluated with the HFL Combinative Distance-based Assessment (CODAS) method. A comparative analysis with HFL COPRAS and HFL TOPSIS is applied. Lastly, the potential of this approach is presented through a case study.