List of Articles Reza Tavakkoli Moghaddam

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  1 - Controlling the Bullwhip Effect in a Supply Chain Network with an Inventory Replenishment Policy by a Robust Control Method
  mahdi Ghaffari Nikbakhsh Javadian Reza Tavakkoli-Moghaddam
  10.22094/joie.2014.283
  20.1001.1.22519904.2014.7.16.7.9
  This paper develops a mathematical model using differential equations and considers a bullwhip effect in a supply chain network with multiple retailers and distributors. To ensure the stability of the entire system and reduce the bullwhip effect, a robust control method More

  This paper develops a mathematical model using differential equations and considers a bullwhip effect in a supply chain network with multiple retailers and distributors. To ensure the stability of the entire system and reduce the bullwhip effect, a robust control method and an inventory replenishment policy are proposed. This shows that the choice of the output matrix may reduce the bullwhip effect. It has also observed in the inventory replenishment mechanism may be a negative impact on the robustness of the bullwhip effect. However, the inventory replenishment behavior may lead to the bullwhip effect on the presented model. This means that the complex supply relationships may have a significant role in controlling or reducing the bullwhip effect of fluctuations. Manuscript profile
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  2 - A Stochastic Optimization Approach to a Location-Allocation Problem of Organ Transplant Centers
  Mahshid Ghane Reza Tavakkoli-Moghaddam
  10.22094/joie.2018.266
  20.1001.1.22519904.2018.11.1.8.8
  Decision-making concerning thelocation of critical resource on the geographical network is important in many industries.In the healthcare system,these decisions include location of emergency and preventive care. The decisions of location play a crucial role due to deter More

  Decision-making concerning thelocation of critical resource on the geographical network is important in many industries.In the healthcare system,these decisions include location of emergency and preventive care. The decisions of location play a crucial role due to determining the travel time between supply and de//////mand points and response time in emergencies.Organs are considered as highly perishable products,whosevarietyof each product has a specific perish time. Despite the importance of this field,only a small proportion of healthcare sector is dedicated to this field. Matching and finding the best recipient for a donated organ is one of the major problems in this field, which is also crucial for the overall organ transplantation process.Balancing the demand and supply in a transplant organ supply chain in order to decrease the waiting list needs certain scheduling and management.The main contribution of this paper consists of considering recipient regionsas another component of the supply chain;in addition,importance of transportation time and waiting lists hasled us to consider a bi-objective model. In addition, uncertainty of input data has led us to consider a stochastic approach. Manuscript profile
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  3 - A simulated annealing algorithm to determine a group layout and production plan in a dynamic cellular manufacturing system
  Reza KiA Nikbakhsh Javadian Reza Tavakkoli-Moghaddam
  20.1001.1.22519904.2014.7.14.4.2
  In this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment with considering production planning (PP) decisions. This model incorporates with an extensiv More

  In this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment with considering production planning (PP) decisions. This model incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. There are also some features that make the presented model different from the previous studies. These include: 1) the variable number of cells, 2) machine depot keeping idle machines, and 3) integration of cell formation (CF), GL and PP decisions in a dynamic environment. The objective is to minimize the total costs (i.e., costs of intra-cell and inter-cell material handling, machine relocation, machine purchase, machine overhead, machine processing, forming cells, outsourcing and inventory holding). Two numerical examples are solved by the GAMS software to illustrate the results obtained by the incorporated features. Since the problem is NP-hard, an efficient simulated annealing (SA) algorithm is developed to solve the presented model. It is then tested using several test problems with different sizes and settings to verify the computational efficiency of the developed algorithm in compare to the GAMS software. The obtained results show that the quality of the solutions obtained by SA is entirely satisfactory in compare to GAMS software based on the objective value and computational time, especially for large-sized problems. Manuscript profile
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  4 - An Integrated Approach for Facility Location and Supply Vessel Planning with Time Windows
  Mohsen Amiri Seyed Jafar Sadjadi Reza Tavakkoli-Moghaddam Armin Jabbarzadeh
  10.22094/joie.2018.544109.1517
  20.1001.1.22519904.2019.12.1.13.0
  This paper presents a new model of two-echelon periodic supply vessel planning problem with time windows mix of facility location (PSVPTWMFL-2E) in an offshore oil and gas industry. The new mixed-integer nonlinear programming (MINLP) modelconsists ofa fleet composition More

  This paper presents a new model of two-echelon periodic supply vessel planning problem with time windows mix of facility location (PSVPTWMFL-2E) in an offshore oil and gas industry. The new mixed-integer nonlinear programming (MINLP) modelconsists ofa fleet composition problem and a location-routing problem (LRP). The aim of the model is to determine the size and type of large vessels in the first echelon and supply vessels in the second echelon.Additionally,the location of warehouse(s),optimal voyages and related schedules in both echelons are purposed.The total cost should be kept at a minimum and the need of operation regions and offshore installationsshould be fulfilled.A two-stage exact solution method, which is common for maritime transportation problems, is presented for small and medium-sized problems. In the first stage, all voyages are generated and in the second stage, optimal fleet composition, voyages and schedules are determined. Furthermore, optimal onshore base(s) to install central warehouse(s)and optimal operation region(s) to send offshore installation’s needs are decided in the second stage. Manuscript profile
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  5 - Planning for Medical Emergency Transportation Vehicles during Natural Disasters
  Hesam Adrang Ali Bozorgi-Amiri Kaveh Khalili-Damghani Reza Tavakkoli-Moghaddam
  10.22094/joie.2020.688.1455
  20.1001.1.22519904.2020.13.2.13.9
  One of the main critical steps that should be taken during natural disasters is the assignment and distribution of resources among affected people. In such situations, this can save many lives. Determining the demands for critical items (i.e., the number of injured peop More

  One of the main critical steps that should be taken during natural disasters is the assignment and distribution of resources among affected people. In such situations, this can save many lives. Determining the demands for critical items (i.e., the number of injured people) is very important. Accordingly, a number of casualties and injured people have to be known during a disaster. Obtaining an acceptable estimation of the number of casualties adds to the complexity of the problem. In this paper, a location-routing problem is discussed for urgent therapeutic services during disasters. The problem is formulated as a bi-objective Mixed-Integer Linear Programming (MILP) model. The objectives are to concurrently minimize the time of offering relief items to the affected people and minimize the total costs. The costs include those related to locations and transportation means (e.g., ambulances and helicopters) that are used to carry medical personnel and patients. To address the bi-objectiveness and verify the efficiency and applicability of the proposed model, the ε-constraint method is employed to solve several randomly-generated problems with CLEPX solver in GAMS. The obtained results include the objective functions, the number of the required facility, and the trade-offs between objectives. Then, the parameter of demands (i.e., number of casualties), which has the most important role, is examined using a sensitivity analysis and the managerial insights are discussed. Manuscript profile
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  6 - Solving a Multi-Item Supply Chain Network Problem by Three Meta-heuristic Algorithms
  Amir Fatehi Kivi Esmaeil Mehdizadeh Reza Tavakkoli-Moghaddam Seyed Esmaeil Najafi
  10.22094/joie.2020.1866273.1648
  20.1001.1.22519904.2021.14.2.10.3
  The supply chain network design not only assists organizations production process (e.g.,plan, control and execute a product’s flow) but also ensure what is the growing need for companies in a longterm. This paper develops a three-echelon supply chain network probl More

  The supply chain network design not only assists organizations production process (e.g.,plan, control and execute a product’s flow) but also ensure what is the growing need for companies in a longterm. This paper develops a three-echelon supply chain network problem including multiple plants, multiple distributors, and multiple retailers with amulti-mode demand satisfaction policy inside of production planning and maintenance. The problem is formulated as a mixed-integer linear programming model. Because of its NP-hardness, three meta-heuristic algorithms(i.e., tabu search, harmony search and genetic algorithm) are used to solve the given problem. Also, theTaguchi method is used to choose the best levels of the parameters of the proposedmeta-heuristic algorithms. The results show that HS has abetter solution quality than two other algorithms. Manuscript profile
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  7 - An integrated crew scheduling problem considering reserve crew in air transportation: Ant colony optimization algorithm
  Saeed Saemi Alireza Rashidi Komijan Reza Tavakkoli-Moghaddam Mohammad Fallah
  10.22094/joie.2022.1934788.1885
  A Crew Scheduling Problem (CSP) is a highly complex airline optimization problem, which includes two sub-problems, namely Crew Rostering Problem (CRP) and Crew Pairing Problem (CPP). Solving these problems sequentially may not lead to an optimal solution. To overcome th More

  A Crew Scheduling Problem (CSP) is a highly complex airline optimization problem, which includes two sub-problems, namely Crew Rostering Problem (CRP) and Crew Pairing Problem (CPP). Solving these problems sequentially may not lead to an optimal solution. To overcome this shortcoming, the present study introduces a new bi-objective formulation for the integrating CPP and CRP by considering the reserve crew with the objectives of crew cost minimization and crew reserve maximization. The integrated model generates and assigns pairings to a group of crew members by taking into account the rules and regulations about employing the manpower (i.e., crew member) and crew reservation in order to reduce flight delays or even cancellations due to the unexpected disruptions. An Ant Colony Optimization (ACO) algorithm is used to solve the considered problem. To justify the efficiency of this proposed algorithm in solving the presented model, different test problems are generated and solved by ACO and GAMS. The computational results indicate that solutions obtained by the proposed ACO algorithm have a 2.57% gap with the optimal solutions reported by GAMS as optimization software on average and significantly less CPU time for small-sized problems. Also, ACO obtains better solutions in significantly shorter CPU time for large-sized problems. The results indicate the efficient performance of the proposed algorithm in solving the given problems. Manuscript profile
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  8 - Fuzzy Particle Swarm Optimization Algorithm for a Supplier ClusteringProblem
  esmaeil Mehdizadeh reza Tavakkoli Moghaddam
  This paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. During recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decis More

  This paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. During recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. In general, many quantitative and qualitative factors, such as quality, price, and flexibility and delivery performance, must be considered to determine suitable suppliers. The aim of this study is to present a new approach using particle swarm optimization (PSO) algorithm for clustering suppliers under fuzzy environments and classifying smaller groups with similar characteristics. Our numerical analysis indicates that the proposed PSO improves the performance of the fuzzy c-means (FCM) algorithm. Manuscript profile