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Despite the key role of start-ups in economic development and job creation, one of the biggest problems of these start-up businesses is their legendary failure rate. One of the main reasons for the failure of these businesses is marketing limitations in the form of lack of financial resources, time, market knowledge and marketing expertise. Also, these companies lack strategic plans and their management is based on personal experience and business intuition. Entrepreneurial networking is one of the solutions that have been proposed to solve these limitations, because networking is considered to be the factor of restructuring the world trade architecture. The current research was conducted with the aim of explaining the role of entrepreneurial networking ability on the marketing performance of start-ups, taking into account the role of entrepreneurial orientation and market knowledge. The statistical population was 550 start-ups and fledgling businesses in Isfahan. The sample size was calculated using the Krejci and Morgan table of 225 companies that were selected by simple random sampling. A standard questionnaire was used to collect research data. Validity of the questionnaire was confirmed by experts and reliability using Cronbach's alpha coefficient. Data analysis was done using structural equation modeling with partial least squares approach and SmartPLS software to test fit and relationships between variables. According to the research results, entrepreneurial networking ability plays an important role in improving the marketing performance of start-up businesses; Therefore, managers who want to increase their marketing performance must identify and form strategic alliances faster than competitors.

The current research was conducted with the aim of designing a dynamic, responsive and competitive structure model for IRI Railway Company.The research method was mixed exploratory (qualitative-quantitative).The statistical population in the qualitative part is high and middle managers of IRI Railway Company, professors of railway engineering,transportation engineering and public administration in higher education centers and specialists related to the subject,and in the quantitative part,employees of IRI Railway Company in The company was in the northeast of the country in 2023.In the qualitative section,20 experts were surveyed using a semi-structured and structured checklist,and in the quantitative section, a 119-item researcher-made questionnaire was distributed among 327 people using a multi-stage relative cluster sampling method.To determine the validity in the qualitative phase,the content of the checklist was approved by experts,and in the quantitative phase,the validity of the questionnaires was confirmed by three

form,content and structure.The reliability of the quantitative and qualitative part of the instrument was also confirmed.Qualitative data were analyzed with Delphi technique in SPSS software and quantitative data were analyzed with structural equation modeling technique and exploratory and confirmatory factor analysis tests,Friedman,Spearman and single sample T in Smart PLS software.The results of the qualitative part indicated that the final model has 9 dimensions,27 components and 119 indicators as described by "intelligence and agility","human and non-human capital","non-technical factors","creativity and knowledge governance","laws and policies","non-financial performance","business structure","technical and technological factors" and "national and international strategies".The results of the quantitative part also showed that all dimensions and components of the research model were confirmed.

The current research was conducted with the aim of designing the optimal model of equity management in order to increase social welfare with a comparative approach.The research method was mixed exploratory(qualitative-quantitative).The statistical population in the qualitative part of university professors in the field of public administration,managers of the Ministry of Economic Affairs and Finance,senior managers of the privatization organization and provincial equity investment companies at the country level and in the quantitative part,top and middle managers,deputies and senior experts of the privatization organization,the organization Stock Exchange,Ministry of Economic Affairs and Finance and provincial investment companies were equity shares in 2023.In the qualitative section,25 experts were surveyed using a semi-structured and structured checklist,and in the quantitative section,a 108-item researcher-made questionnaire was distributed among 169 people using a stratified sampling method.To determine the validity in the qualitative phase,the content of the checklist was approved by experts,and in the quantitative phase,the validity of the questionnaires was confirmed by three

form,content and structure.The reliability of the quantitative and qualitative part of the instrument was also confirmed.Qualitative data were analyzed with Delphi technique in SPSS software and quantitative data were analyzed with structural equation modeling technique and exploratory and confirmatory factor analysis tests,Friedman,Spearman and single sample T in Smart PLS software.The results of the qualitative part indicated that the final model has 6 dimensions,25 components and 108 indicators as "social management","cultural management","economic management","strategic management","educational management" and "political management".The results of the quantitative part showed that all dimensions and components of the research model were confirmed.

Telehealth systems, including patient telemonitoring systems, have consistently faced challenges in user adoption since their introduction. The diversity and conflicts in users' views, needs, and concerns about changes in health service delivery create a complex situation, which can be defined as a "soft problem." Designing these systems requires an approach to understand the issues and complexities and achieve feasible solutions considering the social and cultural conditions of the implementation environment. This research aims to use the modified soft systems methodology framework as a structured method to tackle these soft problems in the design and implementation of patient telemonitoring systems from the perspective of human factors. This research employs a hybrid approach, incorporating soft systems methodology to identify problems, define requirements, and determine actions, alongside the NASSS framework as a theoretical lens to guide participants' views. This approach was used to develop the patient telemonitoring system with a focus on system adoption. The study involved conducting interviews, drawing rich pictures, analyzing users' views, identifying problems during the finding phase, and performing root definition, CATWOE analysis, and presenting conceptual models in the modeling phase. During the discussion and definition phases, based on conceptual models from physicians' and patients' perspectives, desirable and feasible actions were defined. Semi-structured interviews were conducted with 15 physicians and 13 patients, individually and in groups of two and three, as end-users of the patient telemonitoring system. The interview results were analyzed, and participants' views were categorized into four issues: telemonitoring process requirements, trust in the system, cost-effectiveness, and the implementation of the telemonitoring system within the current hospital structure and procedures. In the modeling phase, root definitions were created using the PQR formula and enriched with CATWOE analysis. Conceptual models of the problems were then presented based on patients' and physicians' perspectives. Finally, after the discussion and definition phases, desirable and feasible actions for developing the patient telemonitoring system were defined in four dimensions: expected system features, executive processes, required rules and instructions, and necessary policies. The results show that soft systems methodology, by understanding human factors' perspectives and identifying and conceptualizing the problems and complexities of various aspects of the patient telemonitoring system, can significantly aid system developers, implementers, and health system policymakers. It helps them understand the requirements and agreed processes of potential users before design and implementation, reducing resistance and increasing user adherence.

The smallest disruption in the process of a supply chain can be likened to a fault. A fault whose gap and depth can increase moment by moment. The resiliency of the supply chain of Iran's auto parts manufacturing industry, along with the possibility of dealing with these disturbances, leads to the development of exports in this supply chain. In this regard, this mixed research (qualitative-quantitative) aims to provide a model of the functional factors of sustainable resilience of the supply chain of the parts manufacturing industry. Iran's auto has done it with the approach of export development. First, in the qualitative section, 49 indicators were identified with the help of reviewing valid research records. Then, in the quantitative part, using the Delphi method and a panel of 19 experts, after three rounds, 24 important indicators were selected and the stability of the indicators was also confirmed by the opinion of the experts. In the continuation of the quantitative part of the research, the relationship between the variables was determined to achieve the pattern in the quantitative part by relying on the Interpretive Structural Modeling (ISM) method. The findings of the research were a ten-level model, where the most effective index in the tenth level was the prediction of crises such as unexpected events (storms, hailstorms, earthquakes, floods, droughts) and the most effective index was the speed and ability of emergency response.

During the last decade, many organizations and industries have focused on financial indicators. However, they have recently found that in addition to financial indicators, economic, social and environmental factors should also be considered in the performance of supply chains as sustainability, which also affects the logistics network of the country's automotive industry. However, industries and organizations cannot ignore cost reduction in today's competitive environment. This paper also presents a model for evaluating the performance of a sustainable lean supply chain to improve productivity.

In terms of applied purpose, the present study is a descriptive survey in terms of data collection.

First, 36 indicators of lean supply chain were extracted based on the study of the background of related researches and then using Delphi method, , their sustainability dimensions were domesticated with the help of 18 experts and specialists in the field of supply chain. The identified factors were determined by interpretive structural method, the relations between and performance evaluation indicators of sustainable lean supply chain in the country's automotive industry. The result of this research is to achieve a model for evaluating the performance of sustainable lean supply chain by improving productivity in the Iranian automotive industry consisting of ten levels.

The aims of this paper are to identify and rank the effective criteria and factors for sustainable Supply Chain Management (SCM) in the ceramic and tile industry using a Multi-Attribute Decision Making (MADM) approach. We focus on enhancing performance evaluation in the industry by prioritizing sustainability criteria through a structured decision-making process.

We employ a Multi-Attribute Decision Making (MADM) approach to identify and rank the effective criteria and factors for sustainable Supply Chain Management (SCM) in the ceramic and tile industry and utilizes the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to determine the dependence relationships between sub-criteria, providing a Analysis Network process (ANP) of the interrelationships within the SCM framework.

The results highlight the importance of considering sustainability criteria in SCM practices to improve overall performance and decision-making processes within the industry.

Originality/Value:

 We have identified and ranked the effective criteria and factors for sustainable Supply Chain Management (SCM) in the ceramic and tile industry, aiding in decision-making processes.

Environmental pollution has become one of the most important human concerns. Today, the high volume of industrial waste created by military products, environmental pressures and lack of resources have promoted the manufacturing industries in this field to move towards the implementation of a closed loop supply chain. The main goal of this article is to design a mathematical model to empower the environmental capabilities of the closed loop supply chain. This research is an applied research in terms of purpose and a quantitative research in terms of data and information collection and analysis method. Therefore, a fuzzy mathematical programming model has been designed. The presented model is a 4-objective model, the first objective of which is to minimize emissions, the second objective is to minimize environmental waste, the third objective is to minimize cost, and the fourth objective is to minimize the risk of raw material supply. After designing the model, validation of the model has been done by solving it in small dimensions and then using four algorithms NSGAII, MOPSO, MOACO, MOSA to solve the model in medium and large dimensions and its results have been compared. Based on the results of sensitivity analysis of the model, the response of the model to different parameters has been investigated. The results show that the simultaneous consideration of environmental, economic and risk dimensions in the parameters leads to the improvement of the performance of the closed loop supply chain in terms of empowering the environmental capabilities and profitability.

In today's industrial units, operators monitor equipment performance, and the challenging coordination between units in vast operating environments with high volumes of equipment can lead to irreparable damage. Despite considerable technological advancements in inspection and surveillance, this responsibility can be effectively delegated to smart devices and the Internet of Things (IoT). Furthermore, the emergence of "edge computing" technology has prompted researchers to explore edge-based computing designs due to their numerous benefits. This study presents a combined model of IoT and civilian drones for intelligent monitoring of industrial equipment performance, employing an edge computing approach. The model is specifically investigated through a case study involving wind turbines. The model evaluates the performance of drones for intelligent monitoring of wind turbines in three stages: 1) Detection process, 2) UAV computational evacuation process, and 3) UAV local computation process. Given the dual purpose of the final model, which involves a combination of the aforementioned three steps, a genetic method was employed for problem-solving with negligible sorting. The amplified epsilon restriction method, utilizing random numbers, was also considered, but the combination of genetic and negligible sorting methods outperformed it, particularly in large problems where the enhanced epsilon restriction method struggled to provide timely responses due to the inherent complexity of the problem.

Investment in industrial equipment is a necessity for every industrial unit. In this study, a mathematical model for intelligent monitoring of the performance of industrial equipment of wind turbines using the Internet of Things and unmanned aerial vehicles (UAVs) with an edge computing approach is investigated. In this model, the performance of the UAV for intelligent monitoring of wind turbines is investigated in three stages: detection, computational offloading, and local computations. Considering the bi-objective nature of the final model, the model was solved by a genetic algorithm with non-dominated sorting and the epsilon constraint method using random numbers. According to the findings of the study, the epsilon constraint method loses its efficiency with increasing model dimensions and is not able to find the Pareto frontier in problems with large dimensions. For this purpose, the model was solved using the second version of the genetic metaheuristic algorithm with non-dominated sorting and a new structure for representing chromosomes. This algorithm was able to solve problems in large dimensions that the epsilon constraint method was unable to solve. According to the results, the epsilon constraint method and the genetic algorithm with non-dominated sorting differ only in the time to solve, and have similar performance in other criteria; as a result, the genetic algorithm with non-dominated sorting is proposed as the superior method.

The increased traffic has been followed by many problems in metropolitans, the key of which is air pollution and excessive fuel consumption. Paying attention to public transportation, particularly the bus rapid transit (BRT) system is one of the measures that may be taken, since besides reducing social expenses, it may be very effective in declining air pollution. The main objective of the present research is to study the fuel consumption rate and the emissions rate of various air pollutants including CO2, CH4, and N2O gases in various scenarios of BRT system.

Since traffic and congestion phenomena are complex and dynamic, it is very difficult and sometimes impossible to model them with common mathematical models. To this end, agent-based technologies, highly compatible with these characteristics, can be utilized. In the current research, BRT system’s performance, the fuel consumption rate, and the amount of air pollutants production are estimated using agent-based modeling. This study emphasizes what changes should be made in effective parameters such as bus speed and bus stop time at stations, as well as bus dispatch timing in order to control fuel consumption and reduce pollution factors. This research uses NetLogo software to code the model and run its simulation and considers three different scenarios in line one of BRT system in Tehran (Iran).

following the analysis and comparison of different scenarios, suggestions are made to decline fuel consumption and air pollutants, such as minor changes in the parameters of bus stop times at stations as well as changes in the dispatch time of buses from the terminal in order to reduce fuel consumption and air pollution rates. The results indicate that one of the improved situations was related to the situation of increasing the bus dispatch time parameter and in the bridge scenario, CO2, CH4, and N2O emissions are 1458.6, 1.122, and 11.781, respectively, in one hour of peak passenger time.

According to the results, achieving the goal of reducing fuel consumption and air pollution rates is more suitable in the bridge scenario compared to the other two scenarios. Furthermore, if possible, it is suggested to build bridges at intersections with high traffic, or put the smart traffic light system on the agenda.

The evolution of information technology, artificial intelligence, and large volumes of data in web2, led to the formation of a new approach from the convergence of two scientific fields of business intelligence (BI) and social media analysis (SMA), which is called social business intelligence (SBI) with some researchers. Growing the number of studies in BI and SMA and the explosion of information, required coherence, integration and summary to knowledge extraction. The purpose of this paper is to recognize the capabilities that are the result of the two scientific field convergence. The bibliometric methods have been used to analyze publications tile 2022 and map the topics trend, historical graph, co-occurrence network and knowledge map of social business intelligence capabilities. The results indicate that the nature of business intelligence studies changes toward the analysis of big social media data and integration of analytical and managerial capabilities in BI with the power of marketing, communication and networking in SM. Also, five clusters of social marketing capability, data analytic capability, knowledge capability, communication capability, and transformational capability have been identified for SBI. About the role of SBI in empowering organizations in the digital era, especially in business related to marketing and innovation goals, it is recommended to equip organizations with this technology and its capabilities.

Governments play a significant role in building a constructive environment for the emergence and development of entrepreneurship, which can be achieved through the implementation of entrepreneurship policy. Policy implementation is a link between the formulation and the results of the expected policies. This applied research has been conducted with the aim of designing a model for implementing entrepreneurial policies in Iran. The statistical population of the study consists of experts in the field of entrepreneurship policy, who have been selected by judgmental sampling. The data collection tool is an interview and in order to design this model, we first interviewed 14 experts and implementers of entrepreneurship policies, in order to achieve in-depth theoretical saturation. After collecting and summarizing the interview information, using the theme analysis technique, and open and central coding, 32 indicators to measure 7 factors of standardization, participation in the performance, presenters, performance environment, performance conditions, performance evaluation, and Feedback was identified. Then, in another interview with the same experts who were present in the previous stage of the interview, the pair relationship and two factors were identified and analyzed using the interpretive-structural modeling (ISM) technique, and finally, the relationship and sequence of factors were extracted in a model including 7 dimensions in 5 levels. The obtained results demonstrated that standardization is the basis of the model of implementation of entrepreneurial policies in Iran, which should receive much attention. Moreover, according to the results of this section, the factors of participation in implementation, conditions of implementation, and evaluation in implementation are among the dependent factors, which have a weak influence but high dependence. The feedback factor is the link variable and the standardization factors, executives and implementation environment are independent variables that have high influence and low dependence and are named key variables. According to the factors identified in the research, it is suggested that a national entrepreneurship document and its implementation roadmap be compiled, and in this regard, the opinions and suggestions of executives and beneficiaries should be used both in the actual identification of issues and in providing successful implementation solutions for entrepreneurship programs.

The aim of the current research is to develop a mathematical programming model to provide a resilience considering the quality of response and non-determinism of covid-19. For this purpose, library studies of a three-objective chain model have been designed with regard to the objectives of sustainability and resilience. The first goal includes resilience and cost, and the next two goals include environmental and social responsibility. Then the model was analyzed using NSGA-III meta-heuristic algorithm. The results show that applying resilience and sustainability leads to better use of materials, purchase of less materials, more recycling, and less disposal of materials, which benefits the supply chain. on the other hand, considering the uncertainty in the model, the results show that uncertainty has an effect on all three objective functions and leads to its deterioration. Regarding the realization of accountability, it is concluded that the realization of accountability requires more cost, intensifying environmental issues and of course improving social responsibility. That is, the more social responsibility increases, the more accountability, but increasing accountability requires increasing costs and worsening environmental issues. Finally, the effective strategies for improving the supply chain during the Covid era were examined, and the capacity increase strategies were determined as the best strategies.

The redundancy allocation problem is to find an optimal allocation of redundant components by considering a set of different constraints. Solving these problems is of great interest to various researchers due to its high mathematical complexity. In this research, the satellite attitude determination and control system are studied, and its components are introduced. Then, the reliability and cost of this system are modeled and optimized using a mathematical approach based on redundancy allocation. The model studied in this research pertains to the configuration of a series-parallel system operating within the precise context of a satellite attitude determination and control system. This paper introduces a novel approach to modeling a bi-objective problem and optimizing it using an exact solution method. The mathematical model presented in this paper is a mixed integer non-linear programming (MINLP). In this research, an heuristic method executed in 7 steps has been employed to achieve an exact solution to the problem. Based on this approach, the optimal values for system reliability and cost are determined under various objective weighting schemes.

Recently, supply chains and supply networks are developing towards intertwined supply networks. These new, dynamic structures are different from linear supply chains with static structures and require a revision of some traditional concepts. The aim of this research is mathematical modeling of the three-level supply network (including suppliers, firms, customers) based on resilience. Its approach is quantitative and mathematical modeling. In this research, first the problem is modeled and solved using real data in GAMS software, and after determining the optimal values of the decision variables, the results are analyzed. Also, a sensitivity analysis has been performed on the effective parameter (production capacity). The analysis of the results showed that increase of the capacity parameter did not affect the total cost of the network due to the constant demand. The proposed model, while optimizing the intertwined supply networks, is able to strengthen the resilience of the network in the face of disruption. On the other hand, the effectiveness of the proposed approach has been shown by using it in a case study of the intertwined supply network of tiles and ceramics.

According to the principles of sustainable development, one of the important dimensions of rural sustainable development theories is economic development alongside and overlapping with social and ecological development based on investment approaches. In this study, with the aim of developing rural entrepreneurship, an attempt was made to answer the question "how to improve the performance of the ecosystem and the development of entrepreneurship in rural Iran by studying the mediating role of rural empowerment." It should be noted that this research is applied in terms of purpose Which has been done with a quantitative method of structural equation modeling strategy by partial least squares method with PLS approach. The results show that two currents of cognitive empowerment can lead to the development of rural entrepreneurship. Based on the research findings, several practical suggestions, including raising awareness about empowerment components at three levels of individual, group and enterprise, were presented to rural businesses.

The timely production of orders and their delivery to the customer is a competitive advantage that makes production systems and becomes customer satisfaction. Balancing the load of orders on work stations, reducing the time of the production period and minimizing the cost of human skills and access to machines can be components in the cases of balance of production lines. In this article, by addressing the above components of the mathematical model, several objectives for checking the online load balance are presented. Solving the mathematical model is done by introducing the combined meta-heuristic algorithm of multi-objective genetics and ant milk, this solution method selects the fittest parents based on the fitness of the initial population by using the feature of selecting the initial population and having the search memory to find quality answers at the right time. produces. The results obtained compared to the previous online load balancing methods show that the production time and load balance on the workstations have been improved.

One of the securities designed to fill the gap created by the elimination of bonds in the Islamic financial market is interest-bearing securities that can help the quantitative and qualitative development of the financial market by using legally authorized contracts. The purpose of this study was to design and explain the pricing model of securities with a capital raising approach. This research is a descriptive research in terms of developmental-applied type and in terms of nature. In this study, using the statistical population that includes Islamic securities issued in OTC Iran and the study sample including interest and rent sukuk, which is in the period of 1393 to 1398, the data collected from the new tools of OTC Iran and Tehran Stock Exchange is evaluated. To test the main hypothesis of the research, a regression model is first introduced. The basic model presented in the present study is to estimate the expected rate of return on profit, is estimated and then tested. . The results show that all the studied variables have a significant effect on the pricing of securities. An increase in nominal value raises the price of securities, but in reality the real value of securities decreases with inflation, which is quite evident in the model of the negative effect on pricing.

Dependency in systems is one of the problems that reliability faces. Dependence increases the probability of failure and can affect the performance of a system; Therefore, it is very important to study and understand the consequences when designing, operating and maintaining the system. Regardless of the dependency, reliability is optimistically estimated and the system fails sooner than expected. In the rail industry, subsystems show a high level of dependence due to their high dynamics and complexity. Failure of any of the subsystems can affect the performance of the entire network and sometimes have irreparable consequences. Identifying dependencies and dependent failures based on the block diagram of reliability and the structure of the rail system can affect the more accurate prediction of reliability and reduce the subsequent consequences. This paper presents a new mathematical model for predicting reliability in the rail industry by considering common cause failure. Various methods have been introduced to estimate the common cause failure coefficient. The results show an increase in accuracy in predicting reliability.

This paper presents a systematic and comprehensive analysis procedure for predicting the reliability of the railway industry in order to identify the factors affecting the reliability and obtain a more accurate estimate. This study will also help railway industry managers to better understand the importance of reliability and optimize important performance indicators in the railway industry and to understand the advances that can be made to improve reliability in the railway industry. This study also presents a comprehensive allocation framework with regard to the features of a passenger railway system and possible alternatives; In addition to system reliability, the proposed process can allocate life cycle costs and service reliability to determine the optimal investment plan for designing or updating the rail system. This comprehensive approach can help the rail industry in predicting the reliability of systems and subsystems and identifying the ideal balance between cost, reliability and timing of passenger trains in order to achieve optimal rail system design.

Today, due to the increase in global competition and environmental uncertainty, the success of companies depends on creating value for stakeholders, especially shareholders, and creating wealth for them, and this issue is only possible in the shadow of the analyzing of strategic factors in the internal and external environment; On the other hand, the importance of value creation for small and medium-sized companies is twofold with regard to their long-term sustainability goals. The present study is applied research in terms of the type of use and descriptive-correlational research based on structural equation modeling in terms of data collection. The statistical population of the research includes experts and managers of small and medium enterprises. Experts' Cronbach's alpha coefficient was used to confirm the validity of the questionnaire and to determine its reliability. Data analysis was performed with SPSS software and Smart PLS. The results of data analysis showed that the 5 hypotheses of the present study are confirmed and significant at the 95% level. The highest path coefficient is related to the effect of value creation on the maximum wealth of shareholders with 0.981.

Facility location along with taking account the competition is a critical component of strategic planning. The location affects the competitiveness and market share of new entrants, in long-term. Because of the complications of location problems, most of the location models are faced whit many different limitations. In this paper a competitive facility location model with three competitors which produce two commodities is developed. The problem is modeled in the form of a location-price game. A bi-level model is developed to investigate the location and price. In location-pricing models, the location decision should come before the pricing game. From the second level and the use of Nash equilibrium, equilibrium will be obtained. In this paper, probabilistic costumer behavior with the help of exponential function is modeled. A metaheuristic based on tabu search is proposed to search the optimal location-price solution of the model. Findings show that changing the equilibrium price affect the profitability of new entry firms.

Facility location whit taking account the competition is a critical component of strategic planning. The location affects the competitiveness and market share of a new entry firms, in long term life. In order to develop a model with more realistic characters, demand is supposed elastic. In this research, demand is defaulted with the help of an exponential function. In this paper a competitive facility location model whit two competitors which produce a commodity with elastic demand is developed The problem is modeled in the form of a location-price game. A bi-level model is developed to investigate the location and price, in location-pricing models, the location decision should come before the pricing game. From the second level and the use of Nash equilibrium, equilibrium will be obtained. In this paper, probabilistic costumer behavior whit the help of exponential function is modeled. A metaheuristic based on tabu search and Simulated annealing algorithm are proposed to search the optimal location-price solution of the model. The analysis shows that price game is more intense when incomes of consumers are lower or there are more substitution products.

The main solution for companies to simultaneously achieve economic and environmental goals is to implement a closed loop supply chain. The main goal of this research is to design a mathematical model to empower the environmental capabilities and profitability of the closed loop supply chain in military industries. The presented model is a 4-objective model, the first objective of which is to minimize emissions, the second objective is to minimize environmental waste, the third objective is to minimize cost, and the fourth objective is to minimize the risk of raw material supply. After designing the model, validation of the model has been done by solving it in small dimensions and then using four algorithms NSGAII, MOPSO, MOACO, MOSA to solve the model in medium and large dimensions and its results have been compared. Based on the results, the parameters of the model have been adjusted and the response of the model to different parameters has been investigated. The results show that simultaneous consideration of environmental and economic dimensions in the parameters leads to the improvement of the performance of the closed loop supply chain in terms of empowering the environmental capabilities and profitability.