جاوید قهرمانی نهر

Production planning, scheduling, and sequencing form the core functions of manufacturing companies. The evolving and fluctuating market demands have turned production into a challenge, as companies must deliver high-quality products using minimal resources while responding to uncertain market demands. Therefore, the need for efficient production planning, scheduling, and sequencing has become a crucial research area for both companies and researchers in recent decades. This paper addresses the modeling and solution of a production planning and scheduling problem related to human-robot collaboration under fuzzy conditions. The proposed model aims to determine optimal decisions such as production quantity, human-robot allocation for product manufacturing on each line, processing time, and product production scheduling. To achieve integrated decisions for production planning and scheduling in human-robot collaboration, three objective functions are considered: maximizing the net present value, minimizing the maximum completion time of product manufacturing, and minimizing the total early and tardy times.

Since demand quantity and processing time are considered uncertain parameters in this problem, a pessimistic fuzzy programming approach is used to handle these parameters. To solve the three-objective model, the epsilon-constraint method, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multi-objective Particle Swarm Optimization (MOPSO), and Multi-objective Whale Optimization Algorithm (MOWOA) are applied. Thus, for solving the problem in small sizes and performing sensitivity analysis of the mathematical model, the epsilon-constraint method is used, while for solving larger-sized problems, metaheuristic algorithms are employed.

The analysis of the mathematical model under uncertainty reveals that reducing the maximum completion time of product manufacturing decreases both the net present value and the total early and tardy times. Controlling the model using fuzzy programming and the uncertainty rate also shows that increasing this parameter leads to a reduction in net present value and an increase in the maximum completion time of product manufacturing. Furthermore, analyzing various numerical examples of different sizes indicates that the solution quality of the MOWOA, NSGA-II, and MOPSO algorithms is superior to that of the epsilon-constraint method. Among these algorithms, MOWOA achieves the highest number of efficient solutions with the smallest branch distance metric and the shortest distance from the ideal point.

The analyses indicate that the highest total early and tardy times occur when the uncertainty rate is set at 0.5. Additionally, sensitivity analysis of the bank interest rate shows that a 4% increase in the interest rate results in a 15.68% reduction in the net present value. The bank interest rate has no impact on the maximum completion time of product manufacturing or the total early and tardy times. The analysis of numerical examples with various sizes also demonstrates that the epsilon-constraint method is incapable of solving larger numerical examples, and the quality of the results obtained from metaheuristic algorithms is superior to that of the exact method. Moreover, the number of efficient solutions, the widest spread, and the solution time are better in the metaheuristic algorithms than in the epsilon-constraint method. Among the metaheuristic algorithms, MOWOA exhibits superior performance compared to other solution methods.

Today, due to international sanctions, fierce competition, the prevention of fraud, and competition between goods producing units, the importance of data and information networks has led to pushing goods-producing units to use Internet of Things tools. Supply chain management systems have widely developed smart tools as a platform for the production and storage of big data, facilitating communication between various components and enhancing their overall security. This paper aims to introduce a mathematical model that utilizes Internet of Things tools connected to the blockchain, leveraging artificial intelligence (AIoT) to reduce costs, prevent fraud, and enhanc supply chain security. Considering the importance of medicine fraud, a mathematical model was implemented using artificial intelligence algorithms in a real case study of the pharmaceutical supply chain. The results of solving the mathematical model showed that Internet of Things tools have led to 8.5% profitability in operating costs related to fraud detection and drug security, despite the increase in total costs. Also, the numerical examples showed that the gray wolf algorithm has a higher efficiency in achieving optimal results. The average time to solve the mathematical model with genetic algorithm is 106.46 seconds, with particle swarm optimization algorithm is 111.39 seconds, and with gray wolf algorithm is 123.64 seconds .Gray wolf algorithm has resulted in a 0.5% improvement in total supply chain costs with a 16% increase in resolution time. The proposed model can be useful to prevent fraud and increase the security of Iran's food or pharmaceutical supply chain.

Since the purpose of the current research is to formulate development strategies and improve the productivity of human resources in the organization of JDEVS, this study first identifies and calculates the strengths, weaknesses, opportunities and threats of human resources and then presents development strategies and formulates programs Operations and measures in accordance with the strategies in the organization have been discussed. In this regard, people have been gradually selected from among managers, experts and specialists of the Organization of Academic Jihad of Science and Industry. The technique used to analyze the results is also the approach of strategic reference points. The results of the findings show that the main and general strategy of the organization is an aggressive strategy. Also, after examining the evaluation matrix of internal and external factors in the functional areas of human resources and the opinions of experts in the field of analyzing the internal and external factors of the organization's human resources, with the investigations carried out and also considering the direction of the policy. Identified in this field, human resource strategies were formulated in the SWOT matrix. The obtained results indicate that the strategy is suitable for the main and specialized jobs in the queue, the specialized staff and general staff jobs in the organization, the committed strategy, the suitable strategy for public service jobs, the secondary strategy and the suitable strategy for certain work contract jobs, the strategy It is contractual.

In addition to playing an important role in creating economic security and investment development, insurance companies also invest. The country's insurance industry as one of the country's financial institutions has a special place in the investment process and special attention to appropriate investment policies in the field of insurance industry is essential. So that the efficiency of this industry in allocating the existing budget stimulates other economic sectors. This study seeks to model investment in the performance of dynamic networks of insurance companies.

In this paper, a new investment model is designed to examine the dynamic network performance of insurance companies in Iran. The designed model is implemented using GAMS software and the outputs of the model are analyzed based on regression method. The required information has been collected based on the statistics of insurance companies in Iran between 2012 and 2019.

After evaluating these units, out of 15 companies evaluated, 6 companies had unit performance and were introduced as efficient companies. The average efficiency of insurance companies is 0.78 and the standard deviation is 0.2. The results show that the increase in the value of investments is due to the large reduction in costs and in terms of capital and net profit of companies is a large number that has a clear and strong potential for insurance companies.

Originality/Value:

 In this paper, investment modeling is performed to examine the performance of dynamic networks of insurance companies in Iran.

Productivity can be studied from different dimensions such as energy efficiency, capital, manpower, equipment, etc. Productivity of human resources is one of its most important dimensions and the correct use of other resources also depends on its productivity. Identifying and describing productivity indicators in different dimensions is one of the basic steps of productivity management. This is especially important in scientific and technological organizations. In the current study, the statistical population includes managers and experts of scientific and technological organizations. In this article, the mentioned indicators, with a sample size of 350 were reviewed through a questionnaire using qualitative methods of content analysis and content analysis and confirmatory factor analysis using MAXQDA, SPSS and AMOS software. The results revealed five general indicators: "effective and efficient planning", "financial and technological factors", "motivation, commitment and teamwork spirit","competitiveness and development" and "knowledge, skills and system thinking" as the most important indicators of human resource productivity in scientific and technological organizations. The indicator of knowledge, skills and system thinking has the lowest coefficient and that of effective and efficient planning has the highest coefficient in the final model. Accordingly, to increase the productivity of their human resources, scientific and technological organizations should pay special attention to team building skills, development of decentralized decision processes, strengthening the spirit of participation along with factors such as improving the quality of equipment, technologies and financial issues.

Eenterprise architecture is a concept for organizing and classifying relevant information in a field that the framework is used as a reference for preparing layers of Enterprise architecture. Due to conflicting functions, lack of proper coordination between components, lack of proper integration and redundant processes in organizations; Infrastructure engineering and enterprise architecture is essential and vital for organizations to operate with maximum efficiency. In this research, Zachman framework has been used for engineering the technological infrastructure of the administrative and public affairs department of the East Azerbaijan ACECR. The present study is applied in terms of purpose and survey-analytical in terms of data collection method. The statistical population is all the personnel of East Azerbaijan ACECR. The statistical sample of the representatives introduced in the East Azerbaijan ACECR units is. This research has been done in 4 phases. In phases 1 and 2, the first and second layers of enterprise architecture have been completed by identifying processes, documenting and modeling processes through specialized interview sessions. In Phase 3, during the preparation of the enterprise architecture maturity questionnaire, the impact layer of data and information layer, information technology and business through Smart PLS software is presented. In the final phase, the Zachman model presented for managing administrative and public affairs, which the main processes of the organization are in, and has more communication with other units, in the field of planning, the organizational model and the system model. The results of engineering the technology infrastructure of the organization are to provide the desired strategies in order to improve the current situation. Also, by examining the effect of data and information layer, information technology and business layer on the state of architectural maturity of the organization, information technology with a path coefficient of 0.227, access to information and data with a path coefficient of 0.399 and business processes were observed. Working with a path coefficient of 0.367 has a positive and significant effect on organizational maturity. Finally, it can be said that the implementation of enterprise architecture in the University Jihad Organization improves the level of effective indicators in management and technology.

Over the past thirty years, logistics has undergone tremendous change from a purely operational performance that led to sales or production and focused on securing supply and delivery lines to customers, with the transformation of intelligent technologies into a professional operator. In today's world, the fourth generation of industry has forced companies to rethink how their supply chain is designed. In this case, in addition to the need for adaptation, supply chains also have the opportunity to reach operational horizons, use emerging digital supply chain business models, and transform the company into a digital supply chain. One of the transformational technologies that has had a tremendous impact on the supply chain in this regard is IoT technology. This technology, as one of the largest sources of data production, can facilitate supply chain processes in all its dimensions. However, due to the presence of the Internet and the location of supply chain components in the context of information networks, this digital supply chain always faces major challenges. Therefore, in this paper, an attempt was made to examine and prioritize the most important challenges of implementing a supply chain 0/4 using a nonlinear hierarchical analysis method. In order to investigate these challenges, the opinions of experts active in the supply chain of Fast-moving consumer goods industries (FMCG) were used as a case study as well as some academic experts.The results show that the lack of technological infrastructure and security challenges are the most important challenges of implementing supply chain 0/4 in the era of digital developments, which should be given special attention for a successful implementation.

In this paper, a humanitarian logistics network is designed considering the purchase contract in conditions of uncertainty. Due to the importance of such networks in the event of unforeseen events, the designed model seeks to determine the central and local warehouses as well as shelters to transport the injured. Also, determining the optimal amount of inventory and the correct way of transferring items and injured are other network decisions. In this article, the contract for purchasing items before and after the accident is concluded with suppliers in order to supply raw materials to the severity of the accident.

Due to the uncertainty in the model, the robust optimization method is used to control the uncertainty, and due to the NP-Hardness of the model, the new Gray Wolf-Genetics Algorithm (GGWA) is used to solve the model.

The results show that contract operation has reduced the costs of the entire humanitarian logistics network. The comparison of the means of the objective function and the computational time shows the high speed of the GGWA algorithm in finding near-optimal solutions compared to the PSO and GA algorithms.

In this paper, a new model of humanitarian supply chain network has been designed, which has obtained very favorable results from the problem using the GGWA algorithm in the shortest time.

We present a mathematical model for the problem of collaborative production system based on order with fairness to allocate production loads. The main objectives of the model are to minimize total production costs and maximize the use of resources in order to distribute production loads fairly in conditions of uncertainty. Fuzzy programming was used to control uncertain parameters. The results show that, with increasing the uncertainty rates, production system costs have increased. Since the capacity of factories is constant, with the increase in demand, the amount of production has increased and the maximum use of resources of each factory has also increased. Also, contrary to the trend of system cost changes, with the increase in the number of factories, the maximum use of available resources has decreased. To solve large sample problems, the NSGA II algorithm with a suitable chromosome is used to search the problem space. Numerical results of solving 15 sample problems show the high efficiency of NSGA II algorithm in solving the problem of cooperative production system in a very short time.

In recent years, with the growth of sustainable development as well as the growth of textual tools on information technology, supply chain agility has become very important as a powerful tool to compete in the business environment. In such an environment, supply chain stakeholders expect digital developments and efficient tools to play a role in these supply chain developments; Therefore, this tool, namely the Internet, can play a key role in agility and accelerate activity in the supply chain and create value in the organization. Given the importance of the supply chain and its prominent role as a core in industrial activities, the purpose of this study is to provide a framework for implementing an agile supply chain based on big data from the Internet of Things.

This research is of developmental and applied type and has been done qualitatively. In this study, the components affecting supply chain agility are identified based on big data from the Internet of Things and the conceptual framework of agile supply chain is presented.

The results of the research provide a framework that intelligently identifies the agility needs of the organization and strives to achieve it, thus creating a more competitive advantage for the company and increasing customer satisfaction and expanding the market share of the organization.

This framework can be an effective guide to implementing an agile and clean supply chain based on the use of big data.

With the expansion and intensification of competition, supply chain management has become one of the key issues facing economic firms, as all the activities of organizations to produce products, improve quality, reduce costs and provide services required by customers, has been affected. In this research, a closed loop supply chain network include levels of (manufacturing centers, demand zones, collection centers and disposal centers) under certainty is considered. The main objective of this paper is to determine the optimal number and location of potential facilities and determine the optimal flow considering the minimization total supply chain network cost. To solve this model, a new metaheuristics algorithm called the whale Optimization algorithm has been used with novel priority-based encoding. Also, to demonstrate the high efficiency of the proposed method, 21 sample problems were designed in small, medium and large sizes, and the results obtained from the solving method and the results obtained from the methodology for solving the subject literature were compared. Comparisons between solving methods with consideration of the two averages of the objective functions and the average computational time indicate the efficiency of the proposed solution method for the comparison of the other methods of solving.

cooperatives play a pivot role in creating sustained society. The objective of cooperative movement in developing countries is not only to renew old economical methods, but also to create fair economic and social conditions. For example, in the agriculture sector of most of these countries, small and even moderate agricultural units do not have acceptable productivity and efficiency and are not able to have production with reasonable prices. Therefore, one of the most effective ways for reaching to a successful agriculture development pattern and finally realizing the large-scale objectives of development is to organize people in groups known as “agricultural production cooperatives (APCs)”. Hereby, economic growth, production increase and fair distribution of incomes can be achieved by practical cooperation of rural population in various civil and social activities. Indeed, these cooperatives pave the way for boosting the production and fair distribution of interests by providing a favorable ground for institutionalizing the cooperation of rural population. All the cooperatives do not act in the same way even if they are located in the same country and are governed by the same laws. Studies showed that successful Iranian cooperatives have longer organizational history and more members, grant greater credits and inputs to their individual members, earn greater income, get more benefits, and incorporate more small scale farmers.

in this study, Questionnaire has been used for information collection. The questionnaire is validated after some revisions following consulting with professionals and experts. The reliability of the questionnaire is confirmed by Cronbach's Alpha (α = 0.971) and its validity is confirmed by professional and experts view. Finally, an interpretative equation (ISM) is used to analyze the results of the findings and presenting a sustainable development model for agricultural production cooperatives. ISM is an interactive learning process. In this technique, a set of different directly and indirectly related elements are structured into a comprehensive systematic model. The so formed model portrays the structure of a complex issue or problem in a carefully designed pattern implying graphics as well as words. In other words, interpretive structural modeling (ISM) is a well-established methodology for identifying relationships among specific items, which define a problem or an issue8. For any complex problem under consideration, a number of factors may be related to an issue or problem. However, the direct and indirect relationships between the factors describe the situation far more accurate than the individual factor taken into isolation. Therefore, ISM develops insights into collective understandings of these relationships.

Based on the findings and factors affecting development of cooperatives (economic, social-cultural, environmental, legal, educational, managerial, marketing, infrastructure, individual and cluster characteristics), variables are classified in 5 different levels and according to relationships, the ISM chart is drawn. After analyzing the MICMAC, the variables are divided into three groups: intrusive, independent and dependent variables. Since the definition of relationships between variables and types of variables can lead to better understanding of the subject and appropriate decision, it is recommended to managers of agricultural production cooperatives to pay attention to each component in order to create sustainable cooperatives.

Based on the findings from theoretical literature and interviews with managers and experts of cooperatives, components that affect sustainable development of agricultural production cooperatives are identified. Then, by using expert opinion and structural-interpretation equation approach, 10 components as the main objectives for sustainable development of agricultural production cooperatives are selected. The results of the analysis show that economic, social-cultural, environmental, legal, educational, managerial, marketing, institutional-infrastructural, personality-individual and clustering factors are effective on sustainable development of agricultural cooperatives. Also, it is important to specify the exact relationship between variables and their ranking in order to provide a model for sustainable development of agricultural production cooperatives. In this regard, structural-interpretive equations have been used. The results show that economic, socio-cultural, environmental and infrastructure-institutional factors are classified as intrusive variables. Legal factors and clustering cooperatives are classified as independent variables. Finally, marketing, educational, managerial, and individual factors are classified as dependent variables. According to the results, economic, institutional- infrastructural, and environmental factors are among most basic factors in the sustainable development of agricultural production cooperatives in East Azerbaijan province. Therefore, it is suggested that strategic action be taken to improve the status quo.

In this paper, a five-level pharmaceutical supply chain network is modeled under uncertainty. Levels of this pharmaceutical supply chain network include raw material supplier, production center, distribution center, Health centers and customers. Also, the objectives of this paper include minimizing the costs of the total supply chain network, minimizing the maximum unmet demand, and maximizing reliability in timely delivery of drugs, by considering the perishable time and the discount on the purchase of raw materials. Decision-making variables are divided into two strategic and tactical categories and, include determining the optimal number and location of potential facilities and determining the optimal amount of drug flow between the selected facilities, respectively. A robust-possibilistic optimization method has been used to control the uncertain parameters, and the hybrid LP-metric method and Monte Carlo simulation approaches have been used to solve the multi-objective model. Finally, by providing a numerical example, the outputs obtained from the solution of the model have been discussed.

Considered the most important organizational capital, human resources productivity can improve organizational productivity and excellence. This study aimed to identify the factors affecting human resources productivity in scientific and technological organizations of the selected countries (Germany, England, Turkey, Taiwan, and South Korea) and evaluate the identified components in the Academic Center for Education, Culture and Research of Iran.

A comparative research approach was first used along with the experiences of scientific and technological organizations of the selected countries to identify and evaluate the most important constituent components of human resources productivity. The structural equation modeling (SEM) technique was then employed to analyze the relationships between the identified components. The statistical population included the experienced managers and deputies of the Academic Center for Education, Culture and Research of Iran, 57 of whom were selected and surveyed through the purposive sampling method in this applied-descriptive survey.

Organizational support, education, organizational culture, job satisfaction, employee motivation, organizational structure, efficient and effective leadership and management, competitiveness, creativity, and innovation were identified as important and effective components of human resources productivity in scientific and technological organizations.

Managers of scientific and technological organizations can enhance organizational productivity by improving, modifying, and change the abovementioned factors. They can also achieve their organizational goals properly to meet their needs and accomplish their important missions.

In today’s world, changes in the economy and industry field occur in higher speed compared to the past time. The main aim of organizations and companies is to preserve and increase the benefit as well as survive in the commercial fields. This matter has caused in large scale because of that companies the globalization, economic activity along with the rapid Increment of the technical and restricted sources to compete closely together. For the companies, the competitive benefits, for example as to become efficient related to the affairs such as supply chain. Additionally, because of governmental rules, green affairs and development the social responsibility concept, management the closed loop supply chain field has attained many research interests. Closed loop Supply chain involve forward and reverse both together and the main aim of it’s design is to mix up the environmental observations with the traditional supply chain using accumulating the used products and operations related to the them as well. In this paper a multi objective, multi period multi product closed loop supply chain mathematical model considering green matters and compensable shortage as well as discounts has been developed. Firstly, closed loop supply chain mathematical model has been solved using three multi objective decision maker methods and numerical results have been reported in large scale. Secondly, regarding to the uncertainty of the parameters, the robust optimization model related to the main model has been formed and solved using multi objective decision maker methods, finally the best method for deterministic and uncertain model using filtering has been chosen.