Journal of Applied Research on Industrial Engineering
Volume:8 Issue: 4, Autumn 2021

China introduces a new strain of coronavirus as a causative of a new respiratory disease after several people contracted an unusual pneumonia in December 2019. The World Health Organization stated that the outbreak of the virus resulted in public health emergencies around the world. Humanitarian supply chain management is concerned with managing the efficient flow of aid materials, information and services and aim to reduce the impact of disaster on human lives. In this paper, provides a ranking for key resources in the humanitarian supply chain in the emergency department of Iranian hospital using hybrid decision-making method under COVID-19 conditions. According to the obtain results, nurses in RK 1, receptionists RK 2, general surgeon RK 3, heart residents RK 4 and pulmonologist RK 5. Hybrid decision-making method in this paper is an invaluable contribution to the emergency department and medical managers for evaluates of current situation Emergency Department when crisis occur.

In this paper, a framework for optimizing the oil condensate supply chain is modeled using mathematical planning to design and make strategic and tactical decisions. According to this framework, investment and operating costs for oil and gas transmission lines can be minimized to meet the pressure requirements and the transmission network. Also, we can minimize the production of pollutants in the chain-related sectors. In the case under study, all possible decisions are considered to consider the environmental aspects of the supply chain. Therefore, the structure and decisions of the supply chain are generally based on two objective functions, including reducing transmission and maintenance costs and pollution in treatment plants and distribution centers. The proposed model is 95% reliable, which is acceptable reliability, and can estimate goals with only 5% error. Using the proposed model will reduce costs by 31% and emissions by 51%. Also, there will be an 8% increase in the capacity of fields and refineries and an increase in exports by 65%. Using the results obtained from solving the model, we can determine the share of each petroleum product in the cost and each part of the chain in the production of greenhouse gases. According to the results, fuel oil has the highest and oils the lowest. In addition, refineries have the greatest impact, and storage tanks have the least impact on environmental pollution.

The business process turbulence and the increasing competition among business firms have made the environment around organizations much different than before. Knowing the future business paths and moving in their direction in a way that benefits the organization indicates the necessity of marketing research and concepts such as market-centric. This study aims to evaluate the impact of market-centric on organizational performance by emphasizing the mediating role of organizational innovation in the value chain and provide a model for it. This research is a descriptive-survey study. Confirmatory Factor Analysis (CFA) technique has been used to evaluate the significance of regression weight (factor loading) of different constructs of the questionnaire in predicting the relevant items. LISREL statistical analysis software has been used to test the research hypotheses and analysis of structural equations. The statistical population of the study is all managers and employees working in the value chain of poultry industry in Kurdistan province, which 205 samples have been selected based on Cochran's formula. The results of data analysis indicate that the relationship between customer-centric and inter-task coordination with organizational innovation as well as the relationship between pivotal competition and organizational innovation with the financial performance of the organization was confirmed. There is no significant relationship between pivotal competition and organizational innovation, as well as between customer-centric and inter-task coordination with financial performance of the organization. Finally, some suggestions have been made to improve the performance of the poultry industry.

There are many different fields the change point analysis arises. In those cases, the main problem is locating the unknown change points. The aim of this study is to detect location and time of change point in Poisson regression model. We assume for years before and after the change point , then observation  has a Poisson distribution with parameters , respectively. We used several methods for estimation change point in real mortality data by assume Poisson regression model. Using two simulated and real data analysis showed that the change point has been occurred in year 1993 and this confirmed by all methods. Our findings have shown that the change pattern of mortality trend in Iran is related to improvement of health indicators and decreasing mortality rate in Iran.

The production and service functions in the innovation system emphasize producing new products. As any innovation system’s final output must ultimately produce new products and deliver new services, the considered function is essential in the innovation system. This study seeks to extract the challenges and give solutions to improve the production and deliver services in the innovation system. Producing and delivering services does not occur in a vacuum and should occur in a context called the Supply Chain (SC). In this paper, qualified experts were interviewed to discover the challenges and solutions to improve production. Fifteen elite researchers in the innovation field then discussed the results in focus sessions and refined practical solutions after an in-depth review of the extracted information. The role of responsible institutions was determined, and the necessary indicators were extracted to evaluate the factors of innovative production after providing the required infrastructure to achieve production promotion. One of the Fuzzy Multi-Attribute Decision Making (FMADM) techniques is also used to prioritize the discovered solutions based on the importance of influencing the producing promotion. Finally, a model is presented for improving the production and service functions in the innovation system. The results showed the main solution is to collaborate and create efficient integration at different SC levels.

This research is conducted with the aim of providing an effective advertising pattern based on social networks in educational businesses industry. This research is applied in terms of objective and survey-exploratory in terms of approach. The statistical population of this study was a group of experts including senior managers of private sector educational institutions, university professors and marketing consultants familiar with the private educational services industry that in-depth interviews were conducted with them. The selection of experts and doing interview with them continued until the theoretical saturation was reached and then stopped. Snowball sampling method was used in this research and this process continued until reaching the theoretical saturation. 9 interviews were conducted in total. Due to using the data foundation theory in this research, the main data collection tool was unstructured in-depth interviews with experts. Finally, after three open, axial and selective kinds of coding, the conceptual model of the research was designed based on a paradigm model. Also, in this study, using AHP decision method, research variables were prioritized according to experts.

With the increase of news on social networks, a way to identify fake news has become an essential matter. Classification is a fundamental task in natural language processing (NLP). Convolutional neural network (CNN), as a popular deep learning model, has shown remarkable success in the task of fake news classification. In this paper, new baseline models were studied for fake news classification using CNN. In these models, documents are fed to the network as a 3-dimensional tensor representation to provide sentence-level analysis. Applying such a method enables the models to take advantage of the positional information of the sentences in the texts. Besides, analyzing adjacent sentences allows extracting additional features. The proposed models were compared with the state-of-the-art models using a collection of real and fake news extracted from Twitter about covid-19, and the fusion layer was used as the decision layer in selecting the best feature. The results showed that the proposed models had better performance, particularly in these documents, and the results were obtained with 97.33% accuracy for classification on Covid-19 after reviewing the evaluation criteria of the proposed decision system model.

Optimized asset tracking with Radio Frequency Identification (RFID) as a complicated innovation that requires much money to be implemented has become more popular in the healthcare industry. Considering the use of more antennas in each reader, we present a modern heuristic methods, hybrid of Genetic Algorithms (GA) and Simulated Annealing (SA) for the purpose of placing readers in an emergency department of a hospital with an RFID network. In this study, a multi-objective function is developed for the network coverage maximization and the minimization of total cost, tag reader collision, interference, energy consumption, and path loss in a simultaneous way. The proposed algorithm provides savings (on average) in the total cost of the RFID network through the efficient use of three types of readers with one, two and four antenna ports. Additionally, by testing three scenarios, the effect of algorithms in achieving the optimal solution is indicated by the simulated results.  Besides, the results of GA-SA is compared to the results of GA and other existing models in the relevant literature. It is shown that its main advantage is the use of multi-antenna RFID readers, which reduces the total cost of the RFID network and also increase network coverage with fewer readers and antennas. In other words, contributions for the research are proposing a hybrid GA-SA algorithm, developing a multi-objective function, testing the algorithm in a hospital setting, and comparing the results of GA-SA with GA.

Naturally, managers are interested in analyzing the relative efficiency of the production systems with parametric or non-parametric methods. One of the non-parametric methods utilized in recent three decades is a Data Envelopment Analysis (DEA) that can evaluate the relative efficiency of these structures and determine their strengths and weaknesses. In the real world, most production systems have a network structure. So, Network Data Envelopment Analysis (NDEA) is a suitable non-parametric method to evaluate the performance of production processes, which considers the internal processes. In addition to the importance of treating consumed waters and pollutants in environmental protection in today’s world, increasing the profitability of the production unit can be an important motivation to design the proper model to evaluate the performance of these structures in terms of profitability. In this sense, we first introduce a two-stage feedback structure including undesirable factors. Then, by applying the assumption of weak disposability for undesirable factors, a method for analyzing the relative performance of such network structures is given. The focus would be on profitability maximization. Moreover, to illustrate the proposed approach, a real case on the ecological system of 31 regions of China is used.

Due to the increasing importance of marketing, entrepreneurship and the role of organizational structure in their application, the purpose of this research is to predict entrepreneurial marketing using an organizational structure in the insurance industry. For this purpose, for marketing, seven indicators and for organizational structure, three indicators are defined, then prediction of entrepreneurial marketing indicators has been done by organizational structure indicators using lazy learning algorithm. In the proposed method, after predicting each data by K vector from its closest neighbor, the algorithm database is enriched for better prediction of future data. The proposed algorithm is simulated and compared in five different modes by MATLAB software, also, three insurance (Iran, Karafarin and Parsiyan) companies are selected in Mazandaran province. In total, the statistical population in this study is 588 cases. The results of simulation indicate the proper accuracy of entrepreneurial marketing forecasting based on validation parameters MSE and NRMSD. In this research, Lazy Learning method can predict future without modeling the problem with previous information processing.

Contractors help the government in carrying out construction and service projects. To reduce the risks resulting from the preparation and implementation of construction projects, the insurance industries should cooperate to include risk management. Contractors are facing many challenges regarding their insurance. Therefore, in this study, significant attention has been paid to identifying and ranking the challenges of contractor insurance in construction projects. The required information has been collected through the Delphi method and the opinions of experts in contracting companies. To identify the challenges, an open-ended questionnaire was distributed among the experienced insurance officials and 38 challenges have been identified. The relevant challenges formed the basis of a closed-ended questionnaire and the respondents were asked to re-evaluate their accuracy. Then, the approved challenges were the basis of the fuzzy best-worst method for weighing and ranking the related challenges. The results showed that the failure to provide specific consultation to contractors regarding the legal obligations of social security is the most important challenge in the field of contract insurance.

Emotional Intelligence (EQ) is considered as an alternative issue in both fields of psychology and education. Studies that have been conducted in this area illustrate the role of EQ and its components in different aspects of one's life such as academic achievement, occupation, and social relationships. Turning to a view to academic performance measurement, mathematics is considered as a science which can promote the learners' ability in order to respond to the ups and downs of every individual’s life. Most of the previous papers have investigated the relationship between EQ and mathematical Performance. The main feature of those studies were focusing on statistical analysis. To deal with this issue, this study proposes an alternative procedure not only is interested in employing non parametric models, such as Data Envelopment Analysis (DEA), but also provides the statistical analysis to assess the questioned relation. The proposed procedure can serve as an evaluation tool for educational policy and students ‘promotion.  To do so, eighty-one individuals have been selected among Islamic Azad University (Yadegar-e-Imam Khomeini (RAH) branch) engineering students with simple random during the first midterm of academic year 2019-2020. Distributing a standard EQ questionnaire of Bradberry and Greaves [18] reveals EQ and its four components’ scores. The average of three completed math scores have presented mathematical performance quantity. The results of DEA point out no specific pattern between EQ and mathematical performance. The study also reveals that statistical analysis show a similar trend as efficiency analysis method did.

The purpose of this paper is to develop a new Failure Mode and Effect Analysis (FMEA) framework for identification, prioritization and improvement of failure modes. A hybrid multiple criteria decision-making (MCDM) method combining Stepwise Weight Assessment Ratio Analysis (SWARA) and VlseKriterijumska optimizacija I KOm-promisno Resenje (VIKOR) is used to rank the risk of failure modes identified in FMEA. For this purpose, the SWARA method is utilized to obtain the influential weights and then VIKOR technique is employed to give the prioritization levels for the failure modes in safety equipment. A case study of a gas company in Lorestan Province (Iran) is provided to illustrate the potential application and benefits of the proposed FMEA approach. The obtained results show that the new risk priority model can be effective to find high risk failure modes and create suitable maintenance strategies. The proposed FMEA also can overcome the shortcomings, improve the effectiveness of the traditional FMEA and provide useful information to help in managing risks of safety equipment.

Linear Assignment (LAM) is one of the Multi-Attribute Decision Making (MADM) methods that uses integer programming models in the solution process. In this method, only the final priority of the alternatives is determined and the distance between the alternatives is not clear. The purpose of this paper is to modify this method so that instead of the final priority of the alternatives, the final weight of the alternatives is presented. This is done using a linear programming model of Data Envelopment Analysis (DEA). In this paper, we propose a hybrid MADM-DEA method called Linear Assignment Voting (VLAM). The new method is explained with a numerical example. The method will then be implemented on a problem in the real world to demonstrate the application of the method. In this case study, VLAM demonstrates the prioritization of models proposed by experts for the purchase of excavators in a road construction company. Also, based on the results of this method, the weight of the first, second and third priorities are 0.39, 0.35 and 0.26, respectively. These results increase the decision maker's power in making the final decision and choice.