fuzzy best-worst method

There are many indicators and criteria in the effectiveness of skill training so that the trained person can enter the labor. These indicators and sub-indices should have an operational aspect and be weighted and ranked based on modern methods. The purpose of this study is to identify the weight and the rank of these criteria so they can be used in codification and evaluation of educational and skill models. The statistical population of the research consists of 7 managers and administrators of industrial companies, school managers of skills training and experts in the field of developing training courses, technical courses. These people reviewed the research works and interviews at the first place. The indicators and criteria of the research have been identified with experts. Then, using Fuzzy Delphi method, 5 main indicators and 12 sub-indicators have been approved, and at the end, with the fuzzy best -worst method, the ranking of indicators and sub-indicators were calculated. The results show that the criterion of education alignment with employment status is the most important and main indicator. Also, the criterion of participation of business owners in curriculum planning is the most important sub-indicator of the effectiveness of skill training.

Considering that the transportation of hazardous materials is associated with a very high risk of human, natural and environmental damage, in addition to paying attention to the economic aspects of the routing of hazardous materials, more emphasis should be placed on reducing population and environmental risks. In this research, a multi-objective model was designed for the problem of vehicle routing to distribute gasoline to fuel stations in Bushehr province in fuzzy conditions, and safety considerations were emphasized. Therefore, the goal is to find the shortest route while respecting safety and environmental considerations.

Fuzzy logic was used to calculate the risk of the route and the amount of pollution emitted by gasoline vehicles, and to examine the routes in the GIS software and the natural environment, as well as to collect experts' opinions in the form of a questionnaire. To weight the types of risks and objective functions, the best-worst fuzzy multi-criteria decision-making method was used, and to solve the proposed model, the evolutionary algorithm based on improved Pareto intensity was used.

Because in many routing models, the assumption of uncertainty of some parameters seems to be an inevitable assumption. The problems of positioning and routing and the optimal allocation of vehicles are one of the important decisions of organizations because with optimal routing and positioning, optimal allocation of vehicles and then determining the optimal number of cars can reduce an important percentage of related costs. The results of this research show that three optimal solutions on the Pareto frontier have been determined according to the three goals of route travel time, route risk, and the amount of environmental pollution caused by fuel distribution for the route. Also, according to the calculation of the optimal weights for each objective function and the calculation of the weighted average for the Pareto optimal solutions, as well as the field investigation of the proposed route in terms of the presence of accident-prone points and the risk of the route, the Pareto optimal solution was first selected as the optimal route.

Finally, by solving the model and applying weights to the objective functions based on the experts' opinions, the optimal route was identified and introduced. In this research, an attempt has been made to examine innovation from three aspects: theoretical, technical and practical gaps, which can be mentioned as the strengths of the current research compared to other research. From a theoretical point of view, it has been tried to carry out a relatively comprehensive study of factors affecting the routing of the distribution of hazardous materials (such as gasoline) to determine the optimal route. Also, from the technical point of view, the current research is innovative by focusing on combining fuzzy logic with a multi-objective SPEA2 algorithm. Finally, it has been tried to reduce the practical vacuum of previous research in this field by developing optimal routes.

Research and development (R&D) department is an essential and critical section for all organizations, which are eager to actively participate in markets and strategies on R&D management. Today’s investment in this field has been approved and all organizations are aware of its role to increase competitive risk. Improving R&D departments and promoting the efficiency of companies can help a country to move toward knowledge-based economy and also assist to stop illogical exchange currency flow to foreign countries against import of technology transfer from them. A problem in a domestic market is the lack of the R&D strategy to produce new products and promote the customer’s satisfaction level in industrial companies. The objective of this research is to introduce a two-phase decision-making approach to assess R&D strategies in automotive battery industries stressing on the customer’s satisfaction parameter. In the first section, the practical strategies on R&D management and the effective indices of the customer’s satisfaction on R&D strategies are recognized. In the second section, weighting coefficients related to customer’s satisfaction indices are reached by utilizing the fuzzy best-worst method (FBWM) as an effective multi-criteria decision-making (MCDM) method. Moreover, the weight of any individual strategy and their final prioritization is calculated using the analytical method of the interval-valued triangular fuzzy - gray relation analysis (IVTFN-GRA). Based on the results gained from the proposed FBWM, three effective factors in evaluating R&D strategies in an automotive battery industry are recognized. Finally, among the existing strategies, the joint R&D strategy with 0.375 rate is selected

Data in various organizations has become a valuable asset and data governance has become one of the priorities of the organization. A review of previous studies shows that the assessment of the implementation of the data governance system in organizations is done qualitatively and organizations cannot determine a plan to improve their situation based on this type of assessment. The purpose of this paper is to provide a quantitative way to measure the level of implementation of data governance in an organization and subsequently plan to improve the status quo. Due to the qualitative nature of the influential factors in measuring the success rate, fuzzy concepts have been used for modeling and analysis. Also, in order to consider how the factors affect each other, the fuzzy cognitive mapping technique has been used to model the causal relationships between the factors. Then, the identified influential factors have been weighted and prioritized using the best-worst fuzzy method and the DEMATEL technique, and subsequently, scenarios of improving the situation of the organization have been designed to plan for the effective allocation of limited resources of the organization. This research has significant practical implications for the organizations that intend to establish such a system or are in the middle stages of implementation and are looking for a solution to find a plan to improve the situation.

The growing trend of the world towards new technologies and the formation of smart cities, despite their capabilities and benefits, has raised serious concerns about cybersecurity threats and citizens' privacy challenges. Tehran is no exception to this rule in the transition to a smart city. The present paper, in a descriptive survey study, aims to provide a framework for managing cybersecurity and privacy challenges in the transition of Tehran to a smart city. In this research, these challenges are identified by in-depth library studies as well as the implementation of fuzzy Delphi method among a sample of organizational experts (including ten senior managers and relevant officials of the Ministry of Communication and Information Technology, Tehran Municipality Information and Communication Technology Organization, and cyber police). Moreover, the degree of importance (weight) of each challenge is determined by the Fuzzy Best-Worst method (FBWM). The findings of this study indicated the high capability of the proposed framework in identifying and accurately weighting these challenges under uncertainty.

competitive advantage and the survival knowledge-based start-up companies depends on maintaining and enhancing the commercialization of technology, the core of the attention of novice business managers is the evaluation and measurement of the TC. In this research, priority is given to the factors affecting the performance of TC and its evaluation in 50 novice students based on the growth center of Science and Technology Park of Tehran University using the FBWM technique. In order to achieve this goal, a comprehensive overview of the literature of the subject has been used by the experts of the experts including the managers of Tehran University of Science and Technology Park and the top companies of the universities in the growth stage of the park. The results of the research show that the speed of commercialization through the number and timing of acquiring new products is the most important factor in the performance of TC. Also, according to the factors of the scale of technology, with the effective use of patented patents and technical knowledge, the future of the market and the scope of the market from the perspective of the experts have become the next important levels.

Evaluation of marketing channels is a very important and complex task, so far no comprehensive model has been presented in this regard. The present study aims to provide a decision framework for evaluating marketing channels.
With extensive study of literature, effective indicators were identified in the evaluation of marketing channels. Then, the newest multi-criteria decision-making method, fuzzy best-worst method was used to calculate the relative importance of indices. In addition, Fuzzy EDAS technique was applied as a multi-attribute decision-making method to rank distribution strategies in marketing channels. The statistical population of this research consists of directors and experts in the food industry, which due to their limited number, sampling was not performed.
Eight criteria were identified for evaluating marketing distribution channels, including trust, conflict, display, delivery, information exchange, product return cost, coordination cost, and profitability as well. Six types of marketing channels are: highlighting the importance of the sales team, expanding the sales team, distributing value added, ordinary distributors, the exclusive web channel, and the shared web channel.
According to the result of research conducted by a food company, the strategy of expanding the sales team has first ranked among other strategies.