Hesitant fuzzy linguistic TOPSIS method for the electric vehicles’ charging stations location selection problem and an application for Istanbul

2020 ◽  
Vol 39 (5) ◽  
pp. 6391-6406
Author(s):  
Zeynep Tugce Kalender ◽  
Huseyin Selcuk Kilic ◽  
Gulfem Tuzkaya ◽  
Busra Gulnihan Dascioglu
Keyword(s):  
Decision Making ◽  
Electric Vehicles ◽  
Critical Role ◽  
Environmentally Benign ◽  
Location Selection ◽  
Vehicle Type ◽  
Decision Making Problem ◽  
Charging Stations ◽  
Fuzzy Linguistic

The prevalence of environmental studies in the academy has increased in recent years, depending on the adverse effects of global warming on natural resources. Besides various environmentally benign applications, one of the most important instruments on eliminating the negative environmental effects of an increasing population is electric vehicles. There are various topics within the concept of electric vehicles, including the determination of electric vehicle type, routing, network design, and so on. However, in this study, determining the locations of electric charging stations is the main focus. The problem is handled as a multi-criteria decision-making problem with the consideration of the uncertainties in the decision-making environment. Specifically, the judgments of decision-makers play a critical role in the success of decisions, but for a decision-maker, it is usually difficult to express his/her preferences by using only one linguistic term due to the structure of some criteria type. Hence, with the proposed methodology, in this study, criteria are firstly classified as fuzzy and crisp according to their objective or subjective characteristics. Afterwards, besides the utilization of classic techniques for crisp type criteria, probabilistic linguistic terms sets are utilized for fuzzy type criteria with an extended version of TOPSIS. The proposed methodology is used for the comparison of 39 alternative electric charging locations in Istanbul, which is one of the most crowded cities in Europe.

scholarly journals Plasminogen Activator System and Breast Cancer: Potential Role in Therapy Decision Making and Precision Medicine

2016 ◽  
Vol 11 ◽  
pp. BMI.S33372 ◽  
Author(s):  
Adel Gouri ◽  
Aoulia Dekaken ◽  
Khalid El Bairi ◽  
Arifa Aissaoui ◽  
Nihad Laabed ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Precision Medicine ◽  
Plasminogen Activator ◽  
Critical Role ◽  
Multiple Cancer ◽  
Dismal Prognosis ◽  
Plasminogen Activator System ◽  
Pai 1

Shifting from the historical TNM paradigm to the determination of molecular and genetic subtypes of tumors has been a major improvement to better picture cancerous diseases. The sharper the picture is, the better will be the possibility to develop subsequent strategies, thus achieving higher efficacy and prolonged survival eventually. Recent studies suggest that urokinase-type plasminogen activator (uPA), uPA receptor (uPAR), and plasminogen activator inhibitor-1 (PAI-1) may play a critical role in cancer invasion and metastasis. Consistent with their role in cancer dissemination, high levels of uPA, PAI-1, and uPAR in multiple cancer types correlate with dismal prognosis. In this respect, upfront determination of uPA and PAI-1 as invasion markers has further opened up the possibilities for individualized therapy of breast cancer. Indeed, uPA and PAI-1 could help to classify patients on their risk for metastatic spreading and subsequent relapse, thus helping clinicians in their decision-making process to propose, or not propose, adjuvant therapy. This review covers the implications for cancer diagnosis, prognosis, and therapy of uPA and PAI-1, and therefore how they could be major actors in the development of a precision medicine in breast cancer.

scholarly journals Decision Making Support for Local Authorities Choosing the Method for Siting of In-City EV Charging Stations

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4682 ◽  
Author(s):  
Grzegorz Sierpiński ◽  
Marcin Staniek ◽  
Marcin Jacek Kłos
Keyword(s):  
Decision Making ◽  
Electric Vehicles ◽  
Urban Areas ◽  
Minimum Energy ◽  
Initial State ◽  
Local Authorities ◽  
Additional Energy ◽  
Charging Station ◽  
Charging Stations ◽  
Decision Making Support

Development of electromobility in urban areas requires an appropriate level of vehicle charging infrastructure. Numerous methods for siting of charging stations have been developed to date, and they appear to be delivering diverse outcomes for the same area, which is why local authorities face the problem of choosing the right station layout. The solution proposed in this article is to use a travel planner to evaluate the distribution of charging stations over the area of a metropolis. The decision making support is achieved by determining optimal travel routes for electric vehicles according to their initial state of charge for the three selected station siting methods. The evaluation focused on the following three aspects: (1) number of travels that cannot be made (due to the lack of a charging station at a certain distance around the start point), (2) extension of the travel caused by the need to recharge the vehicle on-route, and (3) additional energy consumption by electric vehicles required to reach the charging station (necessity of departing from the optimal route). An analysis of the results has made it possible to determine a solution which is superior to others. For the case study analysed in the paper, i.e., the territory of the Metropolis of Upper Silesia and Dabrową Basin (Górnośląsko-Zagłębiowska Metropolia, GZM), the distribution of charging stations established in line with method I has returned the best results. What the method in question also makes possible is to indicate a safe minimum energy reserve to complete the travel by eliminating situations of unexpected vehicle immobilisation due to on-route energy depletion and by minimising the phenomenon referred to as range anxiety.

An Intelligent Ranking Model for Multi-Criteria Decision Making using Fuzzy Matrix Method

2020 ◽  
Vol 13 ◽  
Author(s):  
Naveen Dahiya ◽  
Pardeep Sangwan
Keyword(s):  
Decision Making ◽  
Matrix Method ◽  
Multi Criteria Decision Making ◽  
Efficient Manner ◽  
Fuzzy Matrix ◽  
Human Thought ◽  
Quantitative Form ◽  
Fuzzy Aggregation ◽  
Decision Making Problem ◽  
Fuzzy Linguistic

Background: In the daily life, one may encounter several problems whose solution is based on the consideration of several criteria altogether. To generate a solution for such problems is in fact a complex task. If one generates a solution, then there is no guarantee that the solution is optimal. It is really challenging to take into account all the criteria at the same time and generate a solution that is optimal. Several techniques have been proposed to solve multi-criteria decision making problems. Methods: In this paper, we propose an intelligent solution to multi criteria decision making problem by means of fuzzy aggregation using matrix method. The proposed method finds application in solving such problems where the criteria are defined in qualitative form (fuzzy linguistic variables) rather than in quantitative form (crisp). A novel application of the proposed approach to rank the employees in an organization is presented in the paper. Results: The proposed method is empirically validated by applying it to find the best employee in a institute of repute. Data collection is done in real time to prove the utilization of proposed approach in a efficient manner. Conclusion: The results obtained after application of proposed method to rank the employees are realistic as it takes into consideration the ambiguity involved in human thought process.

Multi-attribute Group Decision-making (MAGDM) using Fuzzy Linguistic Modeling Integrated with the VIKOR Method for Car Purchasing Model

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Decision Making Process ◽  
Vikor Method ◽  
Decision Making Problem ◽  
Purchasing Model ◽  
The Individual ◽  
Fuzzy Linguistic

The change in the trend of transportation, increasing per capita income, expectation of better lifestyle, easy finance, and reduced cost of the automobile are some of the main factors that enable a commoner to have his/her own car. Therefore, it is essential to comprise such features in cars that offer qualities enabling the ease of consumer’s decision-making and comfort to purchase a car individually. Purchasing a car is a complicated multi-criteria decision-making problem as an individual may have different preferences for different criteria attributes. The attributes may be conflicting in nature depending on the need of the individual customer. Generally, it becomes quite difficult to assign ratings to these attributes based on numeric values. Therefore, the decision-making process relies on an idiosyncratic finding of the decision-makers which is in practice fuzzy with uncertainities. Hence, this article is a case study that deals with a hierarchy MCDM approach in accordance with the fuzzy logic and VIKOR method to solve a car purchasing problem.

AN APPROACH FOR COMBINING LINGUISTIC AND NUMERICAL INFORMATION BASED ON THE 2-TUPLE FUZZY LINGUISTIC REPRESENTATION MODEL IN DECISION-MAKING

2000 ◽  
Vol 08 (05) ◽  
pp. 539-562 ◽  
Author(s):  
F. HERRERA ◽  
L. MARTINEZ
Keyword(s):  
Decision Making ◽  
Linguistic Information ◽  
Loss Of Information ◽  
Linguistic Representation ◽  
Representation Model ◽  
Decision Making Problem ◽  
Linguistic Term ◽  
Multi Attribute Decision Making ◽  
Fuzzy Linguistic ◽  
Transformation Processes

In this paper we shall develop a procedure for combining numerical and linguistic information without loss of information in the transformation processes between numerical and linguistic information, taking as base for representing the information the 2-tuple fuzzy linguistic representation model. We shall analyze the conditions to impose the linguistic term set in order to ensure that the combination procedure does not produce any loss of information. Afterwards the aggregation process will be applied to a decision procedure over a multi-attribute decision-making problem dealing with numerical and linguistic information, that is, with qualitative and quantitative attributes.

Models for Multiple Attribute Group Decision Making Based on the Induced Fuzzy Linguistic Ordered Weighted Harmonic Mean Operator and Their Applications

2016 ◽  
Vol 13 (10) ◽  
pp. 7329-7332
Author(s):  
Hao Zhou ◽  
Tao Tao ◽  
Sheng Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Practical Method ◽  
Harmonic Mean ◽  
Security Evaluation ◽  
Linguistic Variables ◽  
Multiple Attribute ◽  
Decision Making Problem ◽  
Fuzzy Linguistic

In this paper, we investigate the multiple attribute group decision making problem with triangular fuzzy linguistic information. We proposed the induced fuzzy linguistic ordered weighted harmonic mean (IFLOWHM) operator. A practical method based on the FLWHM and IFLOWHM operators is developed for multiple attribute group decision making with triangular fuzzy linguistic variables. Finally, an illustrative example for security evaluation of wireless sensor network is given to verify the developed approach.

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