ملیحه نیک سیرت

In this paper, a Binary Fuzzy Linear Programming Problem (BFLPP) with fuzzy objective function and fuzzy constraints is considered. This paper proposes a new approach that solves the problem based on Kerre's adapted method, which maintains the assumption of being fuzzy in the solving process. Therefore, the solution is more consistent with the uncertainty governing the problem.

This paper proposes a new fuzzy branch-and-bound approach based on Kerre's adapted method to solve the fuzzy binary integer programming problem. In each node of the branch-and-bound tree, the linear relaxation of the fuzzy problem is solved with a new fuzzy simplex method based on Kerre's adapted method.

Numerical examples are presented to illustrate the proposed method step by step, and the results are compared with those of other approaches that solve fuzzy binary integer programming problems.

Originality/Value:

 Unlike the available defuzzification procedures and fuzzy ranking functions in the research problem literature, the proposed approach considers the assumption of being fuzzy in the solution process and thus offers a more realistic solution.

Due to the outbreak of Coronavirus 2019 and the need for social distance, virtual education and online exams have replaced face-to-face education. Thus, the prevalence of corona has led to the consideration of virtual (electronic) education as a necessity in many countries. The purpose of this study is to investigate the effect of virtual education on students' learning. In this research, library information was collected using written and electronic scientific texts. Also, the researcher has considered a questionnaire with 55 questions and 15 components in order to assess teachers 'views and opinions on students' learning in virtual education. In this study, the first secondary schools of Birjand city have been considered and 240 teachers have been selected as a sample. The data collection method was an online questionnaire and sampling was done randomly. SPSS and pls software have been used to analyze the information. Analyzes show that virtual education has no significant effect on students' learning (P ≤ 0.05). However, virtual education has a negative impact on religious growth and moral development, economic and professional education, scientific and technological development, social and political education, biological and physical education, teacher role, educational environment and evaluation. Virtual education has a positive effect on the appropriateness of content and resources, the role of family and environment, the role of information and communication technology and smart tools, the role of educational materials and training time. It seems that despite the advantages of virtual education over face-to-face education, virtual education has no effect on students' learning and the best educational method is a combination of both methods. Due to the fact that in the context of the corona virus epidemic, educational classes are conducted virtually and students experience this educational method, so the study of the effect of virtual education on students' learning seems important and necessary. This article examines the impact of e-learning on various components of students' learning . The results of the study can be used for education experts, teachers and school principals.

In today's world, companies must focus most of their activities and capabilities on customer satisfaction; Because customers are the only source of return on investment. If a company wants to have customer satisfaction, it must be able to measure it. Customer satisfaction provides a fundamental perspective on customer issues and improves organizational performance. In this study, the level of satisfaction of the stakeholders of the South Khorasan Gas Company has been examined.

The research method is descriptive in which the tool used is a questionnaire. Questionnaires were sent to various groups of stakeholders, including gas community representatives, clients, managers, facility neighbors, contractors and suppliers of the South Khorasan Gas Company. After collecting the responses of the stakeholders, the current state of satisfaction of the stakeholders of South Khorasan Gas Company has been investigated with statistical analysis of the results according to the customer satisfaction models. In the end, relevant suggestions are presented to increase the satisfaction of the beneficiaries.

The results showed that satisfaction in the field of clients 94%, neighbors of facilities 89%, managers of National Gas Company 70%, suppliers 89%, executive contractors 80%, service contractors 85% and community representatives 84%.

Originality/Value:

 Measuring customer satisfaction provides an effective tool for controlling the overall performance of organizations and helps the organization to identify its weaknesses and try to eliminate them, and the ability to identify economic advantages according to specific time conditions.

Corona is currently the world's health crisis and the biggest challenge humans have experienced since World War II. Given the epidemic of the disease, it is invaluable to forecasting the number of cases and the resulting deaths to better understand the current situation and provide a short-term plan by managers. Accordingly, in this paper, a neuro-fuzzy network model is proposed to forecast the number of cases and deaths in countries that are most affected by this disease. The performance of the proposed neuro-fuzzy network has been compared with time series forecasting neural network as well as radial basic functions neural networks. The proposed model is able to predict the number of cases and deaths from the disease for a period of the next 15 days at a lower error rate.

After the crisis, one of the most important goals of humanitarian logistics organizations is to transport essential goods to the affected areas as quickly as possible. To this end, decisions must be made on the supply of vehicles and their routing and scheduling. The problem of humanitarian aid transportation after the crisis is of particular importance because of the lack of vehicles, the uncertainty conditions, and the immediate and unpredictable changes. This paper deals with the issue of supply, routing and scheduling of vehicles in uncertain conditions with the aim of delivering the necessary goods within the specified time window to affected locations at the minimum cost. Accordingly, at first, the sources of uncertainty in the post-crisis transport and humanitarian relief problem are extracted, including uncertainties in the cost of using the vehicles, travel time and also fuzzy constraints. Then a fuzzy mixed integer programming model for the problem is proposed that simultaneously incorporates the fuzzy objective function, fuzzy constraints and fuzzy parameters. To achieve a sustainable strategy, fuzzy credibility programming approach has been proposed to deal with uncertainty and provide a solution that can find sustainable strategies against post-crisis environmental changes. The final model is implemented in AMPL optimization software and computational results are presented to evaluate the proposed model and method.

A route guidance system is one of the most important services of advanced traveler information systems (ATIS) for drivers,which aims to inform the state of the highway’s traffic to a group of drivers using variable message sign (VMS), web sites, medias and etc. Dynamic travel time information is one of the major components of the dynamic route guidance system which can increase the highway networks reliability, lighten the traffic flow and create dynamic route guidance for drivers. In this paper different methods are reviewed and the results of neuro-fuzzy neural networks and perceptron neural networks are compared. Comparing the results of these methods for predicting the data collected from the Chamran to Niyayesh ramp in Tehran highway network, shows that fuzzy-neural approach can achieve more accurate results.