Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200730Optimizing a bi-objective vendor-managed inventory of multi-product EPQ model for a green supply chain with stochastic constraints134106604ENSaeide Jamshidpour PoshtahaniDepartment of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, IranSeyed Hamid Reza PasandidehDepartment of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, IranJournal Article20190604In this paper, a bi-objective multi-product single-vendor single-buyer supply chain problem is studied under green vendor-managed inventory (VMI) policy based on the economic production quantity (EPQ) model. To bring the model closer to real-world supply chain, four constraints of model including backordering cost, number of orders, production budget and warehouse space are considered stochastic. In addition to holding, ordering and backordering costs of the VMI chain, the unused storage space cost is also added to the total cost of the chain. To observe environmental requirements and decrease the adverse effects of greenhouse gases emissions (GHGs) on the earth and human’s life, green supply chain is utilized to reduce the GHGs emissions through storage and transportation activities in the second objective function. Three multi-objective decision making methods namely, LP-metric, Goal attainment and multi-choice goal programming with utility function (MCGP-U) are implemented in different sizes to solve the presented model as well. Two multi-criteria decision making (MCDM) approach and statistical analysis are applied to compare the outcomes of three proposed solving methods. GAMS/BARON software is utilized to minimize the values of the objective functions. At the end, numerical examples are presented to represent the application of the mentioned methodology. To come up with more insights, sensitivity analysis is executed on the main parameters of proposed model. Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200810A new methodology for COVID-19 preparedness centers based on a location-allocation platform3541111719ENMohammad Alipour VaeziSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0002-7529-1848Reza Tavakkoli-MoghaddamSchool of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran0000-0002-6757-926XJournal Article20200424COVID-19 disease is spreading all over the planet. It is more than necessary that any researcher does his/her part to control this pandemic disease. Since this virus is infectious, and due to the limitations of hospitals, in different matters, such as human recourses (expertise) and needed equipment, it is reasonable to identify a pre-determined number of hospitals as COVID-19 pandemic centers and trying to equip them as much as possible to treat a relative patient in them. This study proposes a methodology based on a multi-criteria decision making (MCDM) method, namely BWM-WASPAS, for COVID-19 preparedness centers based on a location-allocation problem. This methodology is examined in Tehran city as a real-life case study. We find out that the most important item in this decision making is the ICU capacity. However, ignoring the other criteria is not allowed at all.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200810An efficient centralized master echocardiography schedule in a distributed hospital/clinic network4275106605ENDelaram ChaghazardyFaculty of Industrial and Systems Engineering,Tarbiat Modares University, Tehran, Iran.0000-0002-0844-4947Seyed Hessameddin ZegordiFaculty of Industrial and Systems Engineering,Tarbiat Modares University, Tehran, Iran.Mohammad SepehriFaculty of Industrial and Systems Engineering,Tarbiat Modares University, Tehran, Iran.Hassan AghajaniMD, FSCAI, Associated Professor, Interventional Cardiologist, Department of Cardiology, Tehran Heart Centre, Tehran University of Medical Sciences, Tehran, Iran.Journal Article20191108Appointment scheduling systems are applied in a broad variety of healthcare environments to reduce costs and increase quality of services. This study is concerned with the problem of appointment scheduling in a distributed multi-hospital network of echocardiography departments. In this paper, a centralized master schedule is presented to maximize profit margin through maximizing the number of performed echoes and minimizing overtime. Developing such a schedule requires handling shift scheduling and capacity allocation problems simultaneously. Based on real-world settings, a mixed integer linear programming model is proposed for the research problem. Since this model requires a large amount of time and memory to provide good solutions, and fails to find feasible solutions for most of the test problems, two metaheuristics are proposed with different approaches. The first one is combined variable neighborhood search with simulated annealing (VNS-SA) and the second one is hybrid particle swarm optimization (HPSO). Also two lower bounding techniques based on patients’ assignment ( ) and specialists’ assignment ( ) are presented. Then the efficiency of the proposed model and algorithms is evaluated using a set of practical-sized test problems. The results showed that VNS-SA is capable of providing high quality solutions in reasonable amount of time for all test problems and outperforms HPSO. Furthermore, the superiority of over and the lower bound provided by the mathematical model was shown from both the quality and computational time points of view. Finally, some managerial notes and suggestions for extension are presented.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200813A credit mechanism in coordinating quality level, pricing and replenishment decisions with deteriorating items7691106606ENMahdi Ebrahimzadeh-AfruziSchool of Industrial Engineering, Iran University of Science and Technology, Tehran, IranAlireza AliahmadiSchool of Industrial Engineering, Iran University of Science and Technology, Tehran, IranJournal Article20200201In this paper, we present a two-level supply chain (SC) consisting of a single manufacturer that suppling one type of deteriorating product to a single retailer that the market demand rate for the product is time-varying and depends on two endogenous variables that include the retail price and product quality. The objective of this paper is to determine simultaneously pricing policy and ordering for the retailer, as well as product quality optimizing strategy for the manufacturer. Firstly, the problem is formulated under a decentralized structure with a manufacturer-Stackelberg game where each member optimizes his/her decisions regardless of the others’ profitability. Next, a centralized structure was presented and optimized based upon the whole SC profitability. Although the centralized model improves the quality level of the product and profitability of the entire SC, it may reduce the profitability of each SC members. Then, this paper is developed with an incentive scheme based on credit policy to coordinate this system. Moreover, Numerical examples and sensitivity analysis are presented to indicate the effectiveness of the contract. The results show that the credit contract can lead to perfect coordination, while the coordinated system is more robust than the centralized system. This paper extends the understanding of supply chain coordination in the context of deteriorating items that indisputably have a reciprocal relationship with market time-varying demand in many real-life cases.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200814A closed-loop supply chain network design with considering third party logistics: A case study92110106607ENBeheshteh Moghadas PoorSchool of Industrial Engineering, Iran University of Science and Technology, Tehran, IranMohammad Saeed JabalameliSchool of Industrial Engineering, Iran University of Science and Technology, Tehran, IranAli Bozorgi-AmiriSchool of Industrial Engineering,
College of Engineering, University of Tehran, Tehran, Iran0000-0002-1180-9572Journal Article20200211Organizations are nowadays seeking competitive advantage over other rivals, reduction of costs, and customer satisfaction for their progress and development. One of the key factors in reaching the competitive advantage is to have a robust logistic system. The available complexities in the forward and reverse integration processes lead managers to take the companies offering third party logistics services as proper alternatives for outsourcing processes. Furthermore, with population growth and development of transportation network, the amount of scrap products related to this industry is increasing. One of the widely used products is tire which could cause irreversible damages to the environment if it is not logically and appropriately disposed after being fully used. Accordingly, this study proposed a multi-period, multi-product, bi-objective mathematical model to design a closed-loop supply chain network in the tire industry concerning sustainability factors (economic and social) under the third party logistic management. The proposed model aimed at maximizing the profit made by different process over the scrap products and reaching social sustainability as well. Furthermore, the environmental impacts were controlled. The augmented epsilon-constraint method was implemented to solve the multi-objective model and reach optimal Pareto solutions. Finally, the proposed model was validated against a case study in the tire industry.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200816A reward-penalty stochastic pricing and advertising model under demand uncertainty111135106609ENAtefeh HassanpourDepartment of Industrial Engineering, K. N. Toosi University of Technology, Tehran, IranEmad RoghanianDepartment of Industrial Engineering, K. N. Toosi University of Technology, Tehran, IranReza RamezanianDepartment of Industrial Engineering, K. N. Toosi University of Technology, Tehran, IranJournal Article20200302This paper aims in assessing the effects of governmental policies on a maximal covering location problem facing stochastic demand which is sensitive to both the retail price and facility advertising effort. A reward-penalty two-stage stochastic programming model is proposed to formulate the problem as a supportive approach in a mixed integer non-linear programming form. In particular, a stochastic pricing and advertising dependent demand model in a facility location configuration is developed which sets the retail price for each opened facility and various advertising effort levels based on the zone’s attractiveness. To promote customer welfare and satisfaction, the legislative counterpart of the reward-penalty model is introduced. The legislative model assigns the minimum satisfaction demand level to the model as a constraint. In both models, the firm tries to maximize its net profit according to government decisions. An analytical method based on the L-shaped algorithm is provided to determine the best solutions of the first and second stages with coping nonlinearity term of the proposed models. Finally, numerical examples are developed to illustrate the governmental policies impacts to reach to the most social welfare as well as the least reward-penalty legislation.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200816The structure of stock markets as signed networks136146107843ENMaryam EhsaniElectrical Engineering faculty, Arak University of Technology, Arak, IranJournal Article20200406Dynamism and evolution in financial markets and specifically stock markets represents a complex network with many relations between different finance agents and corporations. So there are many researches analyzing different aspects of stock markets in the field of complex networks. However, studying financial markets as signed networks maybe considered as a new perspective in this area. This paper proposes a new methodology for analyzing structure of stock markets as signed networks in the perspective of balance theory. For this purpose, some stock markets based on some data of Tehran stock market and Nasdaq are modeled as signed networks and some aspects of their structural properties were studied from the point of view of balance theory. The results show the whole pattern of the structure of stock networks approximately fit to a completely balanced structure. It is observed that the distance from structural balance rises abruptly in some unstable duration and so may be proposed as an index for forecasting overall function of stock markets or crisis conditions. The results also imply the existence and role of positive connection between two balanced partitions. The proposed methodology can lead directly to many applications in analyzing, evaluating and forecasting stock markets such as balanced clustering and determining the important companies and relations affecting the overall system function. The applications could be useful for system control and decisions either in micro level such as portfolio investment or macro level and regulating the market.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200818Competition of risk-averse and risk-neutral financial chains under government policy-making147162108171ENRaziyeh Reza-GharehbaghCollege of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, IranAshkan HafezalkotobCollege of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran0000-0002-6637-5716Ahmad MakuiSchool of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran0000-0001-6249-530XMohammad Kazem SayadiICT Research Institute, Iran Telecommunication Research Center, Tehran, IranJournal Article20200326This research analyzes the competition of two risk-neutral and risk-averse centralized financial chains (FCs) while the government regulates the market to prevent the disproportionately costly interest rates by eliminating unreasonable arbitration of transactions. Each FC consists of an investor and a broker, helping to fund the financial needs of the capital-constrained firms. Utilizing the Stackelberg game theory method, we formulate two-level and three-level optimization models for four potential scenarios and create an integrative structure for evaluating scenarios through the perspectives of both FCs’ risk orientations (i.e. risk-neutral and risk-averse) and two policies of the government (i.e., deregulation and regulation to mitigate the effect of arbitration). We found that under the government’s regulation policy, risk-averse FCs cause a lower amount of arbitration than risk-neutral FCs. We also realized that the increased volume of risk-free interest rate results in less arbitration. Results also demonstrate that the regulator can organize the competing FCs in the market by enforcing limits on interest rate and restricting costly interest rates by controlling the impacts of arbitration, which ensures a steady economy and encourages the funding of capital-constrained businesses.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200821Joint optimal inventory control and preventive maintenance policy with stochastic demand163180108174ENParviz FattahiDepartment of Industrial Engineering, Alzahra University, Tehran, Iran0000-0003-3039-2220Samane BabaeimoradDepartment of Industrial Engineering, Alzahra University, Tehran, IranFateme KarimiDepartment of Industrial Engineering, Alzahra University, Tehran, IranElham SabetiSalehDepartment of Industrial Engineering, Alzahra University, Tehran, IranJournal Article20200402Joint optimal inventory control and preventive maintenance is a rich area of academic research that is still in its infancy and has the potential to affect manufacturing systems' performance. Also, due to uncertainties in demand, maintenance and inventory loss are virtually unavoidable. Therefore, determining the optimal amount of inventory storage, the time to create an additional inventory for storage, and the time of maintenance operations is a concern of many manufacturers. In this paper, a joint optimization model has been developed. In which, for the proximity of reality, demand is considered as an uncertain parameter. The strategy is such that the production component is placed under maintenance as soon as it reaches the <em> </em>level or in the event of a malfunction earlier than , stopped system and placed under maintenance and repairs. Inventory of period with level is created, which during maintenance operations, stochastic demand will be provided. Finally, a model for joint optimization of maintenance and inventory control with random failure is used that minimize the cost and create the maximum level of accessibility. A numerical study is conducted to show the effectiveness and applicability of the proposed integrated model. An accurate algorithm is provided to solve the model. The results show that the model is generally sensitive to the cost.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200827A fuzzy multi-objective optimization model for designing a sustainable supply chain forward network: A case study181215108176ENDavood Andalib ArdakaniFaculty of Accounting, Management and Economic, Yazd University, Yazd, Iranhttp://orcid.org/0000-0002-4738-9362Hajar SoleimanizadehFaculty of Accounting, Management and Economic, Yazd University, Yazd, IranSeyed Heydar MirfakhradiniFaculty of Accounting, Management and Economic, Yazd University, Yazd, IranAsieh SoltanmohammadiFaculty of Accounting, Management and Economic, Yazd University, Yazd, IranDavood ShisheboriFaculty of Engineering, Industrial Engineering Department, Yazd University, Yazd, IranJournal Article20191109Global warming in the industry sector have forced political leaders to seek sustainable supply chains. The ceramic tile industry (CTI) is a highly competitive industry which has a major impact on the environment. The aim of the current paper is to present a sustainable supply chain in CTI in order to minimize costs, minimize adverse environmental effects as well as increase social benefits. To do so, a multi-period, multi-product, multi-supplier, multi-objective supply chain has been designed. Quality issue with different technologies and capacity limitations for plants, warehouses and distribution centres are considered.<br /> The framework of the proposed supply chain network involves a forward network from suppliers offering different raw materials and ends by delivering produced items to end users. The objectives are minimizing the total cost (e.g. variable and fixed costs), minimizing environmental hazards (e.g. industrial dusts and carbon dioxide emission), and maximizing social benefits (e.g. job opportunities).<br /> The problem is mathematically formulated by a mixed integer non-linear programming model. This model is solved using a fuzzy goal programming approach. Using a numerical experiment, the proposed model is evaluated in CTI sustainable supply chain model. The results are reported fuzzily and provide three values for each decision variable for a period of two months. In addition, a sensitivity analysis is done on some parameters to appraise the validity and feasibility of the model. The results demonstrate that there should be a balance among the three pillars of sustainability in order to reap economic benefits in addition to considering environmental health. Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120200904A new combination of multi-mode resource-constrained project scheduling and group decision-making process with interval-fuzzy information216239108522ENM. GhasemiDepartment of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, IranS.Meysam MousaviDepartment of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, IranS. ArameshDepartment of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, IranJournal Article20200408Multi-mode resource-constrained project scheduling problem (MRCPSP) is one of the most important extensions of the basic RCPSP. In this paper, a new mathematical model for MRCPSP is presented with a time-quality trade-off approach. The model has two objectives, the first objective minimizes the project completion time, and the second objective maximizes the project quality while the quality of activities can be increased based on the reworking. In addition, in the presented model, total available resources, including renewable and non-renewable, are decision variables. The quality and duration of project activities are interval forms. For this purpose, a new expert weighting method based on interval information is presented to unify the experts’ views. The group decision-making method applies a bi-directional projection measure to the positive ideal solution and two negative ideal solutions. Moreover, a new extended interval-fuzzy solution method based on goal programming is proposed to deal with the interval information and mathematical model objectives. The presented mathematical model and group decision-making method are solved with a dataset, and some sensitivity analyses are reported.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120201014Key success factors for demand response implementation: A hybrid multi-criteria decision making approach240261109864ENSeyyed Mojtaba Hashemi MajoumerdDepartment of Industrial Management and Information Technology, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, IranMostafa ZandiehDepartment of Industrial Management and Information Technology, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran0000-0003-1209-9514Akbar Alem-TabrizDepartment of Industrial Management and Information Technology, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, IranMasoud RabiehDepartment of Industrial Management and Information Technology, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, IranJournal Article20200209Today’s societies need more electricity for sustainable development. But the faster growth in demand than supply has led to governments to face the challenge of secure power provision. Demand response (DR) is a clean and cheap way to overcome this challenge. Many factors contribute to the success of DR programs. These factors have also complex and mutual relationships that make it hard to manage all of them. This study tries to determine the role of factors in success of DR programs and identify the factors that have more leverage effect in this regard. This research integrate Analytic Network Process (ANP) and Decision Making Trial and Evaluation Laboratory (DEMATEL) method to overcome the traditional ANP weakness that assumes influential degrees are equal. The proposed model can assess the interrelationship between the factors and provide a cause-effect diagram to evaluate the implementation policies, as well. The results show that, contrary to current efforts, political and cultural factors are more effective than technological ones.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120201014Application of MCDM methods in managerial decisions for identifying and evaluating future options: A real case study in shipbuilding industry262286114322ENMaryam KeyghobadiDepartment of Industrial and Systems Engineering, Amirkabir University of Technology
(Tehran Polytechnic), Tehran, IranSeyed Hamid Reza ShahabiDepartment of Industrial and Systems Engineering, Amirkabir University of Technology
(Tehran Polytechnic), Tehran, IranMohammadsaeed SeifDepartment of Mechanical Engineering, Sharif University of Technology, Tehran, IranJournal Article20191022In today's competitive world, making appropriate strategic decisions is one of the major challenges industries and businesses facing to create competitive advantages in future. MCDM approaches can provide an integrated framework for identifying, evaluating and prioritizing strategic options. In this article, we put forward a two-stage procedure organized as a hybrid methodology to show the usefulness of various MCDM methods in real-world cases. The first step is related to shaping the future options by MODM techniques, and the second step is concerned with evaluating the options by using MADM techniques (SWARA and G-COPRAS). A numerical example in shipbuilding industry is then carried out to illustrate the efficiency of the proposed methodology. Three scenarios, including “Economic”, “Eco-friendly” and “Midway” are considered for the future of merchant fleets according to the global current status. Based on SWARA implementing results, the "cost" and "employment" criteria are identified as the most important factors in the shipbuilding industry among the 12 identified criteria. According to the presented framework, the “Midway” scenario is given the highest priority. Finally, regarding to the country's situation in shipbuilding, some suggestions have been made in this area.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120201014Distribution system optimization in the field of cosmetic products: A case study287300110913ENBahare JafariDepartment of Information Technology Management, Kharazmi University, Tehran, IranFarzad HaghighiradDepartment of Information Technology Management, Kharazmi University, Tehran, Iran0000-0002-3561-0779Reza Yousefi ZenouzDepartment of Information Technology Management, Kharazmi University, Tehran, IranJournal Article20200225Considering the importance of distributing and selling products through various channels and their different costs, choosing a distribution channel and planning and controlling their operations in order to serve customers is a very important and high efficient affair. Regarding a generalized allocation model, this article has attempted to present a new type of distribution system in the supply chain, so that each one of the distributors can focus more on the retailers and prevent the conflict between distribution channels. A nonlinear multi-purpose mixed-integer programming model with a robust optimization approach has been considered, so that while minimizing distribution costs, the allocation ratio of orders to retailers was also maximized. In the phase of solving the designed model, at first the initial nonlinear model was converted into a linear model and as the model was multi-purpose, the metric LP method has been used for solving small dimensions. Then, to reinforce the model against uncertain parameter changes, the model has been reinforced by considering the demand as an uncertain parameter. The integrated QFD/AHP approach has also been used to evaluate and rank distribution methods, taking into account the important characteristics of the distributors and the retailers' desired criteria regarding distributors.Iranian Institute of Industrial EngineeringJournal of Industrial and Systems Engineering1735-827213120201026Evaluating and prioritizing the failure factors and cause of delays in IT projects using FMEA: Towards project continuity301316110916ENParisa GharibnejadFaculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, IranBakhtiar OstadiFaculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, IranJournal Article20200601Today, the use of information technology and software applications in organizations is inevitable. To maintain competitiveness, companies need to define different projects in IT areas and also need to keep the risk level of the defined projects at an acceptable level. In this paper, it has been tried to develop a framework for assessing the readiness of IT projects by using the relationship between concepts of business continuity management and project management. Therefore, by reviewing the literature on causes of delays and failure factors in IT projects, as well as interviews with some experts and business continuity consultants, essential criteria for delaying and failing IT projects are selected, and the impact of these criteria on each of the five phases of IT project development are checked and prioritized. By presenting the extended formula to calculate the weighted risk priority number according to the Failure mode and effect analysis approach, a framework has been provided for assessing readiness based on the priority level of these criteria.