فهرست مقالات Lot-sizing

• دسترسی آزاد مقاله
  • صفحه چکیده
  • متن کامل
  
  1 - Fuzzy Mathematical Model For A Lot-Sizing Problem In Closed-Loop Supply Chain
  Amir Fatehi Kivi Amir aydin Atashi Abkenar Hossin alipour
  10.22094/joie.2018.268
  The aim of lot sizing problems is to determine the periods where production takes place and the quantities to be produced in order to satisfy the customer demand while minimizing the total cost. Due to its importance on the efficiency of the production and inventory sys چکیده کامل

  The aim of lot sizing problems is to determine the periods where production takes place and the quantities to be produced in order to satisfy the customer demand while minimizing the total cost. Due to its importance on the efficiency of the production and inventory systems, Lot sizing problems are one of the most challenging production planning problems and have been studied for many years with different modeling features. In this paper, we propose a fuzzy mathematical model for the single-item capacitated lot-sizing problem in closed-loop supply chain. The possibility approach is chosen to convert the fuzzy mathematical model to crisp mathematical model. The obtained crisp model is in the form of mixed integer linear programming (MILP), which can be solved by existing solver in crisp environment to find optimal solution. Due to the complexity of the problems harmony search (HS) algorithm and genetic algorithm (GA) have been used to solve the model for fifteen problem. To verify the performance of the algorithm, we computationally compared the results obtained by the algorithms with the results of the branch-and-bound method. Additionally, Taguchi method was used to calibrate the parameters of the meta-heuristic algorithms. The computational results show that, the objective values obtained by HS are better from GA results for large dimensions test problems, also CPU time obtained by HS are better than GA for Large dimensions. پرونده مقاله
• دسترسی آزاد مقاله
  • صفحه چکیده
  • متن کامل
  
  2 - Multiple Items Supplier Selection, Economic Lot-sizing, and Order Allocation Under Quantity Discount: A Genetic Algorithm Approach
  Getachew Basa Bonsa Till Becker Abdelkader Kedir
  10.22094/joie.2023.1901314.1751
  The task at hand involves selecting the most suitable supplier(s), determining the optimal lot size, and allocating the total order quantities among the suppliers based on various selection criteria. However, this can become more complex when taking into account quantit چکیده کامل

  The task at hand involves selecting the most suitable supplier(s), determining the optimal lot size, and allocating the total order quantities among the suppliers based on various selection criteria. However, this can become more complex when taking into account quantity discount offers and transportation selection decisions in the selection and order allocation process. To address this challenge, this paper proposes an integrated approach that combines the Analytic Hierarchy Process (AHP) with a multi-objective mixed integer nonlinear program. The approach is designed for a multi-item, capacitated multi-supplier scenario, where the goal is to select suppliers, determine lot sizes, and allocate orders while taking into account unit quantity discounts and intermodal freight costs. The proposed approach aims to minimize costs and the percentage of rejected items, while maximizing the purchasing value. To solve this problem, an efficient genetic algorithm with problem-specific operators is utilized. پرونده مقاله
• دسترسی آزاد مقاله
  • صفحه چکیده
  • متن کامل
  
  3 - Three Metaheuristic Algorithms for Solving the Multi-item Capacitated Lot-sizing Problem with Product Returns and Remanufacturing
  Esmaeil Mehdizadeh Amir Fatehi Kivi
  This paper proposes a new mixed integer programming model for multi-item capacitated lot-sizing problem with setup times, safety stock and demand shortages in closed-loop supply chains. The returned products from customers can either be disposed or be remanufactured to چکیده کامل

  This paper proposes a new mixed integer programming model for multi-item capacitated lot-sizing problem with setup times, safety stock and demand shortages in closed-loop supply chains. The returned products from customers can either be disposed or be remanufactured to be sold as new ones again. Due to the complexity of problem, three meta-heuristics algorithms named simulated annealing (SA) algorithm, vibration damping optimization (VDO) algorithm and harmony search (HS) algorithm have been used to solve this model. Additionally, Taguchi method is conducted to calibrate the parameter of the meta-heuristics and select the optimal levels of the algorithm’s performance influential factors. To verify and validate the efficiency of the proposed algorithms in terms of solution quality, the obtained results were compared with those obtained from Lingo 8 software for a different problem. Finally, computational results of these algorithms were compared and analyzed by producing and solving some small, medium and large-size test problems. The results confirmed the efficiency of the HS algorithm against the other methods. پرونده مقاله
• دسترسی آزاد مقاله
  • صفحه چکیده
  • متن کامل
  
  4 - A Multi-level Capacitated Lot-sizing Problem with Safety Stock Deficit and Production Manners: A Revised Simulated Annealing
  Esameil Mehdizadeh Mohammad Reza Mohammadizadeh
  [1] Corresponding author e-mail: mehdi.foumani@monash.edu [1] Corresponding author e-mail: mehdi.foumani@monash.edu Lot-sizing problems (LSPs) belong to the class of production planning problems in which the availability quantities of the production pla چکیده کامل

  [1] Corresponding author e-mail: mehdi.foumani@monash.edu [1] Corresponding author e-mail: mehdi.foumani@monash.edu Lot-sizing problems (LSPs) belong to the class of production planning problems in which the availability quantities of the production plan are always considered as a decision variable. This paper aims at developing a new mathematical model for the multi-level capacitated LSP with setup times, safety stock deficit, shortage, and different production manners. Since the proposed linear mixed integer programming model is NP-hard, a new version of simulated annealing algorithm (SA) is developed to solve the model named revised SA algorithm (RSA). Since the performance of the meta-heuristics severely depends on their parameters, Taguchi approach is applied to tune the parameters of both SA and RSA. In order to justify the proposed mathematical model, we utilize an exact approach to compare the results. To demonstrate the efficiency of the proposed RSA, first, some test problems are generated; then, the results are statistically and graphically compared with the traditional SA algorithm. پرونده مقاله