AJA Command and Staff UniversityJournal of Systems Oriented Operations Research2783-14931320251122Identifying and prioritizing effective factors on measuring the success of business and information and communication technology alignmentIdentifying and prioritizing effective factors on measuring the success of business and information and communication technology alignment71782510.22034/jmor.2024.717825ENAlirezaMaddahiUniversityEbrahimNazari FarrokhiUniversity faculty memberJournal Article20250627The purpose of the current research was to identify and prioritize the effective factors on measuring the success of the alignment of business and information and communication technology. During this research, the factors were obtained according to internal and external studies and in four dimensions of common understanding between information technology and business. and work, the capability of information technology department, information technology architecture and information technology governance were categorized. In this research, the proposed method called Fuzzy DEMATEL was implemented in order to identify and prioritize factors affecting the success of business alignment and information and communication technology. The findings showed that in the dimension of common understanding between information technology and business, the factor of senior management's knowledge of information technology is the most effective and the factor of communication between information technology managers and managers of other departments is the most impressible factor. In the dimension of the capability of the information technology department, the information technology efficiency factor is the most effective and the information technology responsiveness factor is the most impressible factor. In the dimension of information technology architecture understanding, the presence of integrated macro architecture in the organization is the most effective factor and the information technology infrastructure flexibility factor is the most impressible factor, and finally in In terms of information technology governance, the existence of information technology strategic planning has been the most effective factor and the budget control factor has been the most impressible factor.The purpose of the current research was to identify and prioritize the effective factors on measuring the success of the alignment of business and information and communication technology. During this research, the factors were obtained according to internal and external studies and in four dimensions of common understanding between information technology and business. and work, the capability of information technology department, information technology architecture and information technology governance were categorized. In this research, the proposed method called Fuzzy DEMATEL was implemented in order to identify and prioritize factors affecting the success of business alignment and information and communication technology. The findings showed that in the dimension of common understanding between information technology and business, the factor of senior management's knowledge of information technology is the most effective and the factor of communication between information technology managers and managers of other departments is the most impressible factor. In the dimension of the capability of the information technology department, the information technology efficiency factor is the most effective and the information technology responsiveness factor is the most impressible factor. In the dimension of information technology architecture understanding, the presence of integrated macro architecture in the organization is the most effective factor and the information technology infrastructure flexibility factor is the most impressible factor, and finally in In terms of information technology governance, the existence of information technology strategic planning has been the most effective factor and the budget control factor has been the most impressible factor.https://www.jmor.ir/article_717825_065fd074aad9e05079785aaedbe6fdc4.pdfAJA Command and Staff UniversityJournal of Systems Oriented Operations Research2783-14931320251122Analysis of Internet of Things applications in the smart supply chainAnalysis of Internet of Things applications in the smart supply chain71782610.22034/jmor.2024.717826ENAsgharHemmatiDepartment of Industrial Engineering, Abhar Branch, Islamic Azad University, Abhar, IranAdelPourghader ChobarDepartment of Science and Technology Studies, AJA Command and Staff University, Tehran, IranMiladAbolghasemianDepartment of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran0000-0002-1341-7855Journal Article20250111Improving the quality of supply chain performance in production sectors, factories and various businesses is one of the most important goals of managers in every country, and the economic future of every country depends on the quality of the performance of these institutions. By connecting items with information technology through embedded smart devices or through the use of unique identifiers and carrier data that can establish intelligent communication with the support of network infrastructure and information systems, the whole production process can be optimized. The Internet of Things provides the possibility for customers to have complete product information from raw materials to production through the Internet and use them to make purchasing decisions. This information can include ingredient information, production process information, information related to the manufacturing company, distributor information, product warranty, or other information required by the customer. For this reason and considering the importance of this topic, this research, has tried to use How to evaluate the fuzzy nonlinear analysis method of Internet of Things applications in the supply chain. Understanding these priorities can help the effective implementation of these systems.Improving the quality of supply chain performance in production sectors, factories and various businesses is one of the most important goals of managers in every country, and the economic future of every country depends on the quality of the performance of these institutions. By connecting items with information technology through embedded smart devices or through the use of unique identifiers and carrier data that can establish intelligent communication with the support of network infrastructure and information systems, the whole production process can be optimized. The Internet of Things provides the possibility for customers to have complete product information from raw materials to production through the Internet and use them to make purchasing decisions. This information can include ingredient information, production process information, information related to the manufacturing company, distributor information, product warranty, or other information required by the customer. For this reason and considering the importance of this topic, this research, has tried to use How to evaluate the fuzzy nonlinear analysis method of Internet of Things applications in the supply chain. Understanding these priorities can help the effective implementation of these systems.AJA Command and Staff UniversityJournal of Systems Oriented Operations Research2783-14931320251122Fractional Lotka-Volterra Parameters Estimation Using a Deep Convolutional Neural NetworkFractional Lotka-Volterra Parameters Estimation Using a Deep Convolutional Neural Network71782810.22034/jmor.2024.717828ENAmir HoseinHadianSchool of Computer Science, Institute for Research in Fundamental Science (IPM), Tehran, IranNaderBiranvandFaculty of Sciences, Imam Ali University, Tehran, IranMohammad TaghiPartoviDepartment of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran.Journal Article20250101In the last decade, fractional calculus has attracted much attention and various fractional models have been developed by researchers. While the numerical simulation of fractional dynamics is very important to study, the parameter recovery of these models has many industrial and scientific applications and there is an overlook to this area in the literature on fractional dynamics. On the other hand, recently, artificial intelligence and deep learning methods have solved most of the challenges of dynamical system parameter recovery and the obtained results in the literature show the outstanding performance of these methods in comparison with other state-of-the-art numerical methods. In this paper, a deep convolutional neural network architecture which is named 'Deep-Inference', is utilized for the problem of parameter recovery of fractional Lotka-Volterra equations. This network is trained on the simulated behavior of the fractional Lotka-Volterra equation that is obtained by fractional Adams-Bashforth-Moulton. The obtained results illustrate the robust and high-precision performance of the proposed algorithm.In the last decade, fractional calculus has attracted much attention and various fractional models have been developed by researchers. While the numerical simulation of fractional dynamics is very important to study, the parameter recovery of these models has many industrial and scientific applications and there is an overlook to this area in the literature on fractional dynamics. On the other hand, recently, artificial intelligence and deep learning methods have solved most of the challenges of dynamical system parameter recovery and the obtained results in the literature show the outstanding performance of these methods in comparison with other state-of-the-art numerical methods. In this paper, a deep convolutional neural network architecture which is named 'Deep-Inference', is utilized for the problem of parameter recovery of fractional Lotka-Volterra equations. This network is trained on the simulated behavior of the fractional Lotka-Volterra equation that is obtained by fractional Adams-Bashforth-Moulton. The obtained results illustrate the robust and high-precision performance of the proposed algorithm.AJA Command and Staff UniversityJournal of Systems Oriented Operations Research2783-14931320251122A Nonlinear Optimization Problem to Find Graphs with Maximum Energy72134510.22034/jmor.2024.721345ENSaraAhmadiDepartment of Mathematics, Faculty of Sciences, University of Qom, Qom, Iran0000-0003-0127-409xGholam HassanShirdelDepartment of Mathematics, Faculty of Sciences, University of Qom, Qom, Iran0000-0003-2759-4606Journal Article20250209The energy of a graph G, denoted by E(G), is defined as the sum of the absolute values of the eigenvalues of the adjacency matrix of graph G. Until now, researchers have not been able to provide a formula for the energy of a graph in terms of graph parameters such as the number of vertices or the number of edges. Therefore, they focused on upper and lower bounds. Over the last 30 years, there has been much interest in this area, leading to the development of many new bounds. The optimal lower bound was introduced, and it was shown that star graphs have the lowest energy of all graphs without an isolated vertex. However, attempts to determine the smallest upper bound have been unsuccessful. In this paper, we take an alternative perspective, focusing on optimization, and present a nonlinear optimization problem to determine the smallest upper bound for the graph energy.AJA Command and Staff UniversityJournal of Systems Oriented Operations Research2783-14931320251214Investigating the Role of Organization Resource Planning (ERP) in Supply Chain Management (Case Study: Iranian Fiber Production Company)73255710.22034/jmor.2025.2049682.1017ENMohammad RezaNasiri Jan AghaDepartment of Science and Technology Studies, AJA Command and Staff University, Tehran, IranAdelPourghader ChobarDepartment of Management, Sohrevardi Higher Education Institute, Qazvin, IranMiladAbolghasemianDepartment of Management, Sohrevardi Higher Education Institute, Qazvin, Iran0000-0002-1341-7855MasoudVaseeiDepartment of Science and Technology Studies, AJA Command and Staff University, Tehran, IranJournal Article20250102Globalization of competition means that manufacturing and marketing companies must rely on their top, middle and bottom partners to survive the business and respond quickly in the business environment, in addition to ensuring their successful operations. Many companies have designed extensive systems to integrate and optimize different business Processes, including logging and production planning, throughout their portfolio. The purpose of this research is to investigate the role of organization resources planning in different aspects of supply chain management in Iranian fiber production company. The data collected for this study were collected through a questionnaire and analyzed using LISREL software. Also, to test the significance of the relationships and fit the obtained measurement models, confirmatory factor analysis, standardized factor loading estimation between components and variables of the statistical analytical model were used. The findings indicate that having information on the organizations resource planning is highly desirable and can explain the internal obtained measurement models, confirmatory factor analysis, standardized factor loading estimation between components and variables of the statistical analytical model were used. The finding indicate that having information on the organizations resource planning is highly desirable and can explain the internal supply chain management mechanism and processes in the sample. The result of this relationship is obtained with a factor load estimate of 1.04 as well as a value of RMSEA=0.40, which is a major goodness-of-fit in structural equating modeling.AJA Command and Staff UniversityJournal of Systems Oriented Operations Research2783-14931320251122Presenting a mathematical model to evaluate the effectiveness of advertising media using imprecise and flexible variables73255810.22034/jmor.2025.2058574.1018ENMehdiAhmadiNezaja Studies and Research CenterJournal Article20250426The choice of advertising media due to the multiplicity of available options, the complexity of the advertising phenomenon and its economic importance is a challenging issue that due to its multiple nature, in this study, data envelopment analysis method is used to evaluate the performance of advertising media is. In data envelopment analysis, it is assumed that the inputs are opposite the outputs. In some situations, certain performance measures can have both input and output roles. These types of performance measures are called flexible measures. On the other hand, in traditional data envelopment analysis models, the amount of all input and output data must be known, which is not always true in the real world. Therefore, in this research, an attempt is made to provide a model that, in addition to assuming the existence of inaccurate data, also considers flexible inputs and outputs. Therefore, the present study is an applied case study in the field case. Also, at the end of the research, the proposed mathematical model is described with the help of real data in the form of a case study.