COMPARISONS OF THE PURCHASING AND PRODUCTION LOT SIZING METHODS
Keywords:
Dynamic Lot Sizing, Production Planning, Inventory ControlAbstract
The objective of this research is to determine optimal purchase and production lot size of each product that meets demand at minimum total cost of purchase and production including purchase costs, set up costs, production costs, and holding costs, and to compare results of total production cost and solving time between the methods of a dynamic lot-sizing production and purchase model and dynamic lot sizing model purchase and production combination of the whole production line. Comparing the results between the two methods shows that the total cost and the solving time of the dynamic lot sizing model production and purchase combination of the whole production line is less than the other method.
Downloads
References
De Bodt, M. A., Gelders, L. F., and Van Wassenhove, L. N. (1984). Lot sizing under dynamic demand conditions: A review. Engineering Costs and Production Economics, 8(3), 165-187.
Bai, Q., and Xu, J. (2011). Optimal Solutions for the Economic Lot-Sizing Problem with Multiple Suppliers and Cost Structures. Journal of Applied Mathematics and Computing, 37(1-2), 331-345.
Wagner, H. M., and Whitin, T. M. (1958). Dynamic Version of the Economic Lot Size Model. Management Science, 89-96.
Silver, E. A. (1978). Inventory Control Under a Probabilistic Time-varying Demand Pattern. AIIE Transactions, 10, 371-379.
Callerman, T. E., and Whybark, D. C. (1977). Purchase Quantity Discounts in an MRP Environment. 8th annual midwest conference. American Institute for Decision Science.
Chang, C.-T. (2006). An acquisition policy for a single item multi-supplier system with real-world constraints. Applied Mathematical Modelling, 30(1), 1-9.
Ghaniabadi, M., and Mazinani, A. (2017). Dynamic Lot Sizing with Multiple Suppliers, Backlogging and Quantity Discounts. Computer and Industrial Engineering, 110, 67-74.
Defersha, F. M., and Chen, M. (2008). A Linear Programming Embedded Genetic Algorithm for an Integrated Cell Formation and Lot Sizing Considering Product Quality. European Journal of Operational Research, 187, 46-69.
Gaafar, L. (2006). Applying Genetic Algorithms to Dynamic Lot Sizing with Batch Ordering. Computers & Industrial Engineering, 51, 433-444.
Defersha, F. M., and Chen, M. (2008). A Linear Programming Embedded Genetic Algorithm for an Integrated Cell Formation and Lot Sizing Considering Product Quality. European Journal of Operational Research, 187, 46-69.
Koken, P., Seok, H., and Yoon, S. W. (2017). A Genetic Algorithm Based Heuristic for Dynamic Lot Sizing Problem with Returns and Hybrid Products. Computers & Industrial Engineering, 119, 453-464.
Teunter, R. H., Bayindir, Z. P., and Van Den Heuvel, W. (2006). Dynamic lot sizing with product returns and remanufacturing. International Journal of Production Research, 44(20), 4377-4400.
Li, X., Baki, F., Tian, P., and Chaouch, B. A. (2014). A robust block-chain based tabu search algorithm for the dynamic lot sizing problem with product returns and remanufacturing. Omega (United Kingdom), 42(1), 75-87.
Sifaleras, A., Konstantaras, I., and Mladenovic, N. (2015). Variable Neighborhood Search for the Economic Lot Sizing Problem with Product Returns and Recovery. International Journal of Production Economics, 160, 133-143.
Carvalho, D. M., and Nascimento, M. C. (2022). Hybrid Matheuristics to Solve the Integrated Lot Sizing and Scheduling Problem on Parallel Machines with Sequence-Dependent and Non-Triangular Setup. European Journal of Operational Research, 296, 158-173.
Chotayakul, S., and Punyangarm, V. (2016). The Chance-Constrained Programming for the Lot-Sizing Problem with Stochastic Demand on Parallel Machines. International Journal of Modeling and Optimization, 6(1), 56-60.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Journal of Srinakharinwirot University (Journal of Science and Technology)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Srinakharinwirot University Journal of Sciences and Technology is licensed Under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International (CC-BY-NC-ND 4.0) License, Unless Otherwise Stated. Please Read Journal Policies Page for More Information on Open Access, Copyright and Permissions.