University of TehranIndustrial Management Journal2008-588510420181222Developing Stochastic Additive Utility Method (UTA) Considering the Possible Dependency among CriteriaDeveloping Stochastic Additive Utility Method (UTA) Considering the Possible Dependency among Criteria5035247048710.22059/imj.2019.269380.1007519FAMahnazHosseinzadehAssistant Prof, Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran0000-0003-1211-3371Mohammad RezaMehrganProf, Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, IraLeiliAghaei MeibodiPhD Candidate, Department of Industrial Management, Alborz Campus, University of Tehran, Karaj, IranEzatollahAbbasianAssociate Prof., Department of Public Management, Faculty of Management, University of Tehran, Tehran, IranJournal Article20181120<strong>Objective: </strong>One of the well-known methods as to Multi Attribute Utility Theory (MAUT) in the field of decision making is Utility Additive Method (UTA), which has been developed over time. Two main deficiencies of such methods are first, ignoring the uncertainty embedded in the values of different criteria and second, disregarding the possibility of dependencies among various criteria. The uncertainty problem, either fuzzy or stochastic, has been discussed in various developments including, fuzzy UTA and stochastic UTA models, respectively. Although it seems unlikely to apply in real world problems, the criteria independency is the primary assumption of all these models. Thus, this paper is aimed at developing stochastic UTA model so as to consider the possibility of dependency among different criteria. <br /><strong>Methods:</strong> In this paper, conditional probability is applied in developing the UTA model, so that the probability of values of each criterion is considered with respect to probable values of other criteria. <br /><strong>Results:</strong> The developed model is presented in 12 steps, and its applicability in practice is shown using a real example based upon the data extracted from three main criteria of stock investments for three petrochemical companies. <br /><strong>Conclusion:</strong> The proposed model addresses the deficiency of ignoring the probable dependencies among criteria in stochastic UTA model, and covers the research gap posed by previous researchers.<strong>Objective: </strong>One of the well-known methods as to Multi Attribute Utility Theory (MAUT) in the field of decision making is Utility Additive Method (UTA), which has been developed over time. Two main deficiencies of such methods are first, ignoring the uncertainty embedded in the values of different criteria and second, disregarding the possibility of dependencies among various criteria. The uncertainty problem, either fuzzy or stochastic, has been discussed in various developments including, fuzzy UTA and stochastic UTA models, respectively. Although it seems unlikely to apply in real world problems, the criteria independency is the primary assumption of all these models. Thus, this paper is aimed at developing stochastic UTA model so as to consider the possibility of dependency among different criteria. <br /><strong>Methods:</strong> In this paper, conditional probability is applied in developing the UTA model, so that the probability of values of each criterion is considered with respect to probable values of other criteria. <br /><strong>Results:</strong> The developed model is presented in 12 steps, and its applicability in practice is shown using a real example based upon the data extracted from three main criteria of stock investments for three petrochemical companies. <br /><strong>Conclusion:</strong> The proposed model addresses the deficiency of ignoring the probable dependencies among criteria in stochastic UTA model, and covers the research gap posed by previous researchers.University of TehranIndustrial Management Journal2008-588510420181222Identifying and Comparing the Priority of Commercialization Services Required for Growing and Developing Companies Based in
Tehran University Science and Technology ParkIdentifying and Comparing the Priority of Commercialization Services Required for Growing and Developing Companies Based in
Tehran University Science and Technology Park5255507053810.22059/imj.2019.264596.1007480FAHashemAghazadehAssociate Prof., Department of Management, Faculty of Management, University of Tehran, Tehran, IranMeysamMohammadiMSc., Department of Business Management, Faculty of Management, University of Tehran, Tehran, IranHoseinZadbarMSc., Department of Business Management, Faculty of Management, University of Tehran, Tehran, IranJournal Article20180917<strong>Objective: </strong>Providing commercialization services in science and technology parks and other institutions facilitating the development of knowledge-based companies has a very important role in the success or failure of the companies based there. The aim of this study was to identify and compare the priority of commercialization services required by growth and development companies based in Science and Technology Park in Tehran University. <br /><strong>Methods:</strong> Commercialization services have been identified through the use of library studies and commercialization services of science and technology parks in Iran and elsewhere in the world. This research was carried out with the help of 227 employees of 93 companies based in the park and employees of the park's commercialization department. Subsequently, these categories and services were ranked using the gradual weighting analysis method (SWARA). <br /><strong>Results:</strong> According to the findings of this research, growth companies have given the highest priority to marketing, financing and investment and educational services respectively, while for development companies, financing and investment services, marketing, contracts and guarantee issues have been ranked as the highest priorities respectively. <br /><strong>Conclusion:</strong> In this research, a two-level model for planning and decision making on the combination of commercialization services offered with regard to the constraints, conditions, capabilities, and objectives of science and technology parks is provided. At the first level, there is the decision making about the priorities within the category of services and at the second level, there is decision making in relation to the priority of each category of services. This model can be used in policy making and planning of science and technology parks in order to improve the provision of commercialization services to growth and development companies. <br /> <strong>Objective: </strong>Providing commercialization services in science and technology parks and other institutions facilitating the development of knowledge-based companies has a very important role in the success or failure of the companies based there. The aim of this study was to identify and compare the priority of commercialization services required by growth and development companies based in Science and Technology Park in Tehran University. <br /><strong>Methods:</strong> Commercialization services have been identified through the use of library studies and commercialization services of science and technology parks in Iran and elsewhere in the world. This research was carried out with the help of 227 employees of 93 companies based in the park and employees of the park's commercialization department. Subsequently, these categories and services were ranked using the gradual weighting analysis method (SWARA). <br /><strong>Results:</strong> According to the findings of this research, growth companies have given the highest priority to marketing, financing and investment and educational services respectively, while for development companies, financing and investment services, marketing, contracts and guarantee issues have been ranked as the highest priorities respectively. <br /><strong>Conclusion:</strong> In this research, a two-level model for planning and decision making on the combination of commercialization services offered with regard to the constraints, conditions, capabilities, and objectives of science and technology parks is provided. At the first level, there is the decision making about the priorities within the category of services and at the second level, there is decision making in relation to the priority of each category of services. This model can be used in policy making and planning of science and technology parks in order to improve the provision of commercialization services to growth and development companies. <br /> University of TehranIndustrial Management Journal2008-588510420181222Developing a Multi-Objective Meta-Heuristic Algorithm to Select Work Model and Staff Scheduling in Petrochemical CompaniesDeveloping a Multi-Objective Meta-Heuristic Algorithm to Select Work Model and Staff Scheduling in Petrochemical Companies5515747048810.22059/imj.2018.263727.1007476FAKhodakaramSalimifardAssociate Prof., Department of Industrial Management, Persian Gulf University, Bushehr, Iran0000-0002-7059-724XMeisamNakhaeiMSc, Department of Industrial Management, Persian Gulf University, Bushehr, Iran.ZahraZareMSc, Department of Industrial Management, Persian Gulf University, Bushehr, IranRezaMoghdaniPhD Candidate, Department of Industrial Management, Persian Gulf University, Bushehr, IranJournal Article20180812<strong>Objective:</strong> In petrochemical companies, the existence of various, long job shifts can endanger the physical and mental health of employees, while having a proper timetable, in accordance with labor laws and policies, can help reduce the consequences of the disruption of their work shifts. The purpose of this research is to develop a model for timing the manpower of petrochemical companies in such a way that, by meeting the requirements of the company and the optimal number of employees in each shift, it can minimize the company's payment costs, and maximize the performance and preferences of the employees. <br /><strong>Methods:</strong> The researchers used integer programming model. Because of the complexity of the issue and the multi-objective nature of the model, to solve the mathematical model, NSGA-II algorithm has been used. In order to obtain a better performance of the algorithm, its parameters were tuned using the Taguchi calibration method. <br /><strong>Results:</strong> Based on the findings from various scenarios, the 21-day working model is better than the 16-day working model. Since the model is multi-objective and is solved using the Pareto's approach, the decision maker can, according to the circumstances, choose one of the optimal Pareto solutions. <br /><strong>Conclusion:</strong> Petrochemicals can apply scientific and optimum operation research approaches and its applications, in order to set up employee work schedules, create work-life balance, reduce work-related fatigue, decrease job burnout and improve their performance and productivity. Although scheduling and selecting the appropriate working model is complicated for petrochemical companies, NSGA-II algorithm can be used as an apt and powerful tool in decision making over choosing best working model.<strong>Objective:</strong> In petrochemical companies, the existence of various, long job shifts can endanger the physical and mental health of employees, while having a proper timetable, in accordance with labor laws and policies, can help reduce the consequences of the disruption of their work shifts. The purpose of this research is to develop a model for timing the manpower of petrochemical companies in such a way that, by meeting the requirements of the company and the optimal number of employees in each shift, it can minimize the company's payment costs, and maximize the performance and preferences of the employees. <br /><strong>Methods:</strong> The researchers used integer programming model. Because of the complexity of the issue and the multi-objective nature of the model, to solve the mathematical model, NSGA-II algorithm has been used. In order to obtain a better performance of the algorithm, its parameters were tuned using the Taguchi calibration method. <br /><strong>Results:</strong> Based on the findings from various scenarios, the 21-day working model is better than the 16-day working model. Since the model is multi-objective and is solved using the Pareto's approach, the decision maker can, according to the circumstances, choose one of the optimal Pareto solutions. <br /><strong>Conclusion:</strong> Petrochemicals can apply scientific and optimum operation research approaches and its applications, in order to set up employee work schedules, create work-life balance, reduce work-related fatigue, decrease job burnout and improve their performance and productivity. Although scheduling and selecting the appropriate working model is complicated for petrochemical companies, NSGA-II algorithm can be used as an apt and powerful tool in decision making over choosing best working model.University of TehranIndustrial Management Journal2008-588510420181222Standalone Credit Rating of the Country's BanksStandalone Credit Rating of the Country's Banks5756067048910.22059/imj.2018.262015.1007461FAM.RezaParsafardPh.D. Candidate, Department of Financial Management, Alborz Campus, University of Tehran, Tehran, IranSaedShirkavandAssistant Prof., Department of Financial Management, Faculty of Management, University of Tehran, Tehran, IranRezaTehraniProf., Department of Financial Management, Faculty of Management, University of Tehran, Tehran, IranS.MojtabaMirlohiAssistant Prof., Department of Financial Management, Faculty of Industrial Engineering & Management, Shahrood University of Technology, Shahrood, IranJournal Article20180714<strong>Objective: </strong>The purpose of this research is to assess the standalone credit rating of banks from the perspective of depositors (bank's external stakeholders) to fulfill their commitments. <br /><strong>Methods:</strong> For this purpose, using ranking models of the standard grand agencies and the CAMELS (Capital Adequacy, Asset Quality, Management, Earnings, Liquidity and Sensitivity) rating system, the ranking indexes were identified, and then applying a fuzzy Delphi method the ranking indices were determined and the banks were rated using the PROMETHEE method (Preference Ranking Organization Method for Enrichment of Evaluations). <br /><strong>Results:</strong> Finally, 32 indicators were selected based on the results of the fuzzy Delphi method and according to experts, the weights of the sub-criteria were considered the same. The Banks, which are used as samples in this research, include 21 banks with permission from the central bank of Iran and accepted in the Tehran Stock Exchange and Over-The-Counter Market of Iran. The banks were evaluated based on their activities from 2012 to 2016. <br /><strong>Conclusion:</strong> Based on the rating outcome, Khavaremiane Bank is considered with the highest credit rank, and the Ayande bank is in the worst situation (the least credit rank) among these banks. <br /> <strong>Objective: </strong>The purpose of this research is to assess the standalone credit rating of banks from the perspective of depositors (bank's external stakeholders) to fulfill their commitments. <br /><strong>Methods:</strong> For this purpose, using ranking models of the standard grand agencies and the CAMELS (Capital Adequacy, Asset Quality, Management, Earnings, Liquidity and Sensitivity) rating system, the ranking indexes were identified, and then applying a fuzzy Delphi method the ranking indices were determined and the banks were rated using the PROMETHEE method (Preference Ranking Organization Method for Enrichment of Evaluations). <br /><strong>Results:</strong> Finally, 32 indicators were selected based on the results of the fuzzy Delphi method and according to experts, the weights of the sub-criteria were considered the same. The Banks, which are used as samples in this research, include 21 banks with permission from the central bank of Iran and accepted in the Tehran Stock Exchange and Over-The-Counter Market of Iran. The banks were evaluated based on their activities from 2012 to 2016. <br /><strong>Conclusion:</strong> Based on the rating outcome, Khavaremiane Bank is considered with the highest credit rank, and the Ayande bank is in the worst situation (the least credit rank) among these banks. <br /> University of TehranIndustrial Management Journal2008-588510420181222Agent-based Simulation of National Oil Products Distribution Company’s Supply Network in the Framework of a Complex Adaptive System in Order to Achieve an Optimal Inventory LevelAgent-based Simulation of National Oil Products Distribution Company’s Supply Network in the Framework of a Complex Adaptive System in Order to Achieve an Optimal Inventory Level6076307049010.22059/imj.2019.259762.1007443FAMahdiHomayounfarAssistant Prof., Department of Industrial Management, Islamic Azad University, Rasht Branch, Rasht, Iran.0000-0002-0490-7481SaeidBaghersalimiAssistant Prof., Department of Administrative Management, Islamic Azad University, Rasht Branch, Rasht, IrBijanNahavandiAssistant Prof., Department of Industrial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran1111-2222-3333-4444KavehIzadi SheyjaniM.A., Department of Executive Management, Faculty of Management and Accounting, Islamic Azad University, Rasht Branch, Rasht, IranJournal Article20180608<strong>Objective: </strong>One of the most important challenges of supply chains is the coordination of inventory policies among supply chain elements including suppliers, manufacturers, and distributors. Accordingly, the current study aims to investigate the achievement of the elements of the petrol distribution system to the optimal level of inventory. <br /><strong>Methods:</strong> At first, the supply network of National Guilan Oil Products Distribution Company is defined as a complex adaptive system and then, this network is simulated using agent-based modeling. The core component of this simulation consists of interactions between agents or members of the supply network in the context of inventory management based on the economic order quantity (EOQ). <br /><strong>Results:</strong> The results of simulation in Net Logo software showed that agent-based modeling of the network in the form of a complex adaptive system leads to better understanding of the behavior of supply chain agents in their achievement to the optimal inventory level and enables them to get the proper estimate of the economic order quantity, re-order point and total cost. <br /><strong>Conclusion:</strong> In summary, it can be seen that the agents in the supply chain have the ability to provide their customers’ needs and will not face lost sales as long as they do not pay extra inventory costs.<strong>Objective: </strong>One of the most important challenges of supply chains is the coordination of inventory policies among supply chain elements including suppliers, manufacturers, and distributors. Accordingly, the current study aims to investigate the achievement of the elements of the petrol distribution system to the optimal level of inventory. <br /><strong>Methods:</strong> At first, the supply network of National Guilan Oil Products Distribution Company is defined as a complex adaptive system and then, this network is simulated using agent-based modeling. The core component of this simulation consists of interactions between agents or members of the supply network in the context of inventory management based on the economic order quantity (EOQ). <br /><strong>Results:</strong> The results of simulation in Net Logo software showed that agent-based modeling of the network in the form of a complex adaptive system leads to better understanding of the behavior of supply chain agents in their achievement to the optimal inventory level and enables them to get the proper estimate of the economic order quantity, re-order point and total cost. <br /><strong>Conclusion:</strong> In summary, it can be seen that the agents in the supply chain have the ability to provide their customers’ needs and will not face lost sales as long as they do not pay extra inventory costs.University of TehranIndustrial Management Journal2008-588510420181222Determining the Optimal Surgical Case-Mix and Capacity Assignment for Surgical Services in Hospitals Using Simulated AnnealingDetermining the Optimal Surgical Case-Mix and Capacity Assignment for Surgical Services in Hospitals Using Simulated Annealing6316507049110.22059/imj.2018.255149.1007413FAAida SadatAjadiMSc., Department of Industrial Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, IranSaeedehKetabiAssociate Prof., Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, IranArezooAtighehchianAssistant Prof., Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, IranJournal Article20180330<strong>Objective: </strong>As a crucial industry,the health system needs both managerial and clinical knowledge to solve its problems. This research studies the strategic planning and capacity allocation in operating rooms considering planning and block scheduling strategies. And then, a combined model for determining the optimal case-mix planning and allocating capacity to surgical services is developed as a stochastic optimal programming to face with the uncertain demand for surgery. The purpose of this model is to minimize undesirable deviations including unsatisfied demand, services overutilization and inactive operating rooms. <br /><strong>Methods:</strong> Because the problem is NP-hard in nature, determining the exact solution for real cases will be difficult exponentially. Therefore, a meta-heuristic simulated annealing algorithm is proposed. The results of the mathematical model using GAMS (COINBONMIN) and simulated annealing method, using MATLAB have been compared. <br /><strong>Results:</strong> The samples have been extracted from a Canadian hospital with 9 surgical services, 110 surgeries, 16 operating rooms and 220 beds. To decrease the number of variables and solve the mathematic model, only a few services, surgeries and operating rooms have been selected. The number of operating rooms not underutilization as studied by both methods for all samples is zero – the optimal. The difference between the optimal values of the objective function obtained from the stochastic goal programming and the simulated annealing method for the samples lies within the range of [0/05, 0/6]. <br /><strong>Conclusion:</strong> A stochastic goal programming model has been proposed to determine the number and composition of surgical operations and allocate capacity to surgical services with regard to uncertain demand. The idea of the proposed model is that by changing the number and composition of surgical cases, undesirable deviations can be minimized<strong>Objective: </strong>As a crucial industry,the health system needs both managerial and clinical knowledge to solve its problems. This research studies the strategic planning and capacity allocation in operating rooms considering planning and block scheduling strategies. And then, a combined model for determining the optimal case-mix planning and allocating capacity to surgical services is developed as a stochastic optimal programming to face with the uncertain demand for surgery. The purpose of this model is to minimize undesirable deviations including unsatisfied demand, services overutilization and inactive operating rooms. <br /><strong>Methods:</strong> Because the problem is NP-hard in nature, determining the exact solution for real cases will be difficult exponentially. Therefore, a meta-heuristic simulated annealing algorithm is proposed. The results of the mathematical model using GAMS (COINBONMIN) and simulated annealing method, using MATLAB have been compared. <br /><strong>Results:</strong> The samples have been extracted from a Canadian hospital with 9 surgical services, 110 surgeries, 16 operating rooms and 220 beds. To decrease the number of variables and solve the mathematic model, only a few services, surgeries and operating rooms have been selected. The number of operating rooms not underutilization as studied by both methods for all samples is zero – the optimal. The difference between the optimal values of the objective function obtained from the stochastic goal programming and the simulated annealing method for the samples lies within the range of [0/05, 0/6]. <br /><strong>Conclusion:</strong> A stochastic goal programming model has been proposed to determine the number and composition of surgical operations and allocate capacity to surgical services with regard to uncertain demand. The idea of the proposed model is that by changing the number and composition of surgical cases, undesirable deviations can be minimizedUniversity of TehranIndustrial Management Journal2008-588510420181222Ranking Solutions to Overcome Barriers to the Adoption of Knowledge Management in the Supply Chain Considering a
Combined Fuzzy Decision-Making Approach (Case Study: SAPCO Company)Ranking Solutions to Overcome Barriers to the Adoption of Knowledge Management in the Supply Chain Considering a
Combined Fuzzy Decision-Making Approach (Case Study: SAPCO Company)6516767049210.22059/imj.2019.210043.1007088FAShayaKakwanPhD. Candidate, Department of Technology Management, Faculty of Management and Accounting, Islamic Azad University , South Tehran, Tehran, IranMahmoudModiriAssistant Prof., Faculty of Management and Accounting, Islamic Azad University, South Tehran, Tehran, IranJournal Article20160618<strong>Objective:</strong> Dispersed nature of supply chain and the subsequent dispersion of the knowledge that exists within these areas indicate the necessity of the use of knowledge management in organizations. The organizations may face many challenges if applying knowledge management strategies as well and the secret behind the organizations’ survival lays in their ability to both identify and solve these challenges. The main objective of this research is ranking the solutions to overcome barriers to the adoption of knowledge management in SAPCO supply chain. <br /><strong>Methods:</strong> Library research method, field studies through questionnaires and experts’ viewpoints were used to collect the data. The expert sample consisting of 12 managers and senior experts of SAPCO were selected. Fuzzy decision-making methods in combination with ANP based on DEMATEL (DANP) and Fuzzy VIKOR methods were used to analyse the data. <br /><strong>Results:</strong> Fuzzy DEMANTEL findings showed that in adoption of knowledge management in the supply chain and in providing solutions to overcome the existing barriers, the most influential barriers are “individual” and “technological” barriers. The results of DANP fuzzy method showed that the sub-category of “Low Data and Information Security” within organizations has the highest priority among the barriers. Using Fuzzy VIKOR, the highest priority among the solutions belongs to the designation of an “Outsourcing Strategy” to improve knowledge integration in the supply chain. <br /><strong>Conclusion:</strong> In supply chain, the sub-category of “Low Data and Information Security” that is among “technological barriers” is caused by “individual barriers” and that is the exact reason why it seems necessary for managers and decision makers to pay more attention to “individual barriers”. It is suggested, by this research, that managers design some outsourcing strategies in order to both improve the situation and eliminate the aforesaid barriers.<strong>Objective:</strong> Dispersed nature of supply chain and the subsequent dispersion of the knowledge that exists within these areas indicate the necessity of the use of knowledge management in organizations. The organizations may face many challenges if applying knowledge management strategies as well and the secret behind the organizations’ survival lays in their ability to both identify and solve these challenges. The main objective of this research is ranking the solutions to overcome barriers to the adoption of knowledge management in SAPCO supply chain. <br /><strong>Methods:</strong> Library research method, field studies through questionnaires and experts’ viewpoints were used to collect the data. The expert sample consisting of 12 managers and senior experts of SAPCO were selected. Fuzzy decision-making methods in combination with ANP based on DEMATEL (DANP) and Fuzzy VIKOR methods were used to analyse the data. <br /><strong>Results:</strong> Fuzzy DEMANTEL findings showed that in adoption of knowledge management in the supply chain and in providing solutions to overcome the existing barriers, the most influential barriers are “individual” and “technological” barriers. The results of DANP fuzzy method showed that the sub-category of “Low Data and Information Security” within organizations has the highest priority among the barriers. Using Fuzzy VIKOR, the highest priority among the solutions belongs to the designation of an “Outsourcing Strategy” to improve knowledge integration in the supply chain. <br /><strong>Conclusion:</strong> In supply chain, the sub-category of “Low Data and Information Security” that is among “technological barriers” is caused by “individual barriers” and that is the exact reason why it seems necessary for managers and decision makers to pay more attention to “individual barriers”. It is suggested, by this research, that managers design some outsourcing strategies in order to both improve the situation and eliminate the aforesaid barriers.University of TehranIndustrial Management Journal2008-588510420181222Integrating Process Planning and Scheduling Taking into Account Multiple Objective Using Constraint PlanningIntegrating Process Planning and Scheduling Taking into Account Multiple Objective Using Constraint Planning6776987055110.22059/imj.2019.260052.1007445FANahidKhorasaniMSc., Department of Industrial Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, IranMajidEsmaelianAssociate Prof., Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, IranJournal Article20180612<strong>Objective: </strong>The purpose of this research was to apply various flexibilities including device, tools, direction toward accessing the device (TAD) flexibilities, and considering the qualitative parameters based on the fuzzy inference system for integrated optimization of process planning and scheduling using the Constraint Programmingapproach. <br /><strong>Methods:</strong> There are many approaches to solving IPPS problems. In this research, because of the multitude of existing variables and the complexity of the solution space, limited planning has been used to solve the problem. At first, the qualitative parameters of the model are calculated based on the fuzzy inferencing system and after providing other inputs and solving the problem using limited planning, an optimal answer will be obtained. <br /><strong>Results:</strong> To evaluate the efficiency of the integrated model, an example in the literature considering three states of short, medium and long due date time, has been solved using IBM ILOG Cplex optimization studio software. <br /><strong>Conclusion:</strong> The results indicated the proper functioning of the limited planning method to obtain optimal solutions in a limited time. In fact, the results of the numerical experiments showed that the proposed model has acceptable performance and the proposed algorithm can efficiently solve IPPS. Finally, we can conclude that it is a very suitable method for integrated optimization of multiple objectives.<strong>Objective: </strong>The purpose of this research was to apply various flexibilities including device, tools, direction toward accessing the device (TAD) flexibilities, and considering the qualitative parameters based on the fuzzy inference system for integrated optimization of process planning and scheduling using the Constraint Programmingapproach. <br /><strong>Methods:</strong> There are many approaches to solving IPPS problems. In this research, because of the multitude of existing variables and the complexity of the solution space, limited planning has been used to solve the problem. At first, the qualitative parameters of the model are calculated based on the fuzzy inferencing system and after providing other inputs and solving the problem using limited planning, an optimal answer will be obtained. <br /><strong>Results:</strong> To evaluate the efficiency of the integrated model, an example in the literature considering three states of short, medium and long due date time, has been solved using IBM ILOG Cplex optimization studio software. <br /><strong>Conclusion:</strong> The results indicated the proper functioning of the limited planning method to obtain optimal solutions in a limited time. In fact, the results of the numerical experiments showed that the proposed model has acceptable performance and the proposed algorithm can efficiently solve IPPS. Finally, we can conclude that it is a very suitable method for integrated optimization of multiple objectives.