Probabilistic Multi-Item Inventory Model for Chemicals in Regional Drinking Water Company
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Keywords:
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PDAM, Inventory Replenishment, Probabilistic Inventory Model
Abstract
Inventory management of chemicals in The Regional Drinking Water Company (Perusahaan Daerah Air Minum, PDAM) is known to play an essential role in ensuring the smooth production of clean water and preventing shortages of chemicals that can affect production. At present, 2 primary models for multi-item inventory replenishment are under consideration by PDAM, namely individual and joint replenishment of items. Therefore, this study aims to evaluate the efficiency and effectiveness of individual and joint replenishment models based on uncertain demand with specific probability distribution. The results showed that a probabilistic inventory model (Q, r) with individual replenishment for chemicals in PDAM was recommended.
References
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Wan, G., Y. Cao, and S. Wang (2022). Evaluation of a Joint Replenishment Policy with Sales-Based Threshold and Stochastic Demand. Computers and Industrial Engineering, 172, 108525.
Wang, L. and H. Chen (2022). Optimization of a Stochastic Joint Replenishment Inventory System with Service Level Constraints. Computers and Operations Research, 148, 106001.
Zhang, J., L. Deng, H. Liu, and T. C. E. Cheng (2022). Which Strategy Is Better for Managing Multi-Product Demand Uncertainty: Inventory Substitution or Probabilistic Selling? European Journal of Operational Research, 302(1), 79–95.
Bahagia, S. N. (2006). Inventory System. ITB Press, first edition.
Castellano, D. and L. C. Santillo (2023). Stochastic Joint Replenishment Problem under a Fill Rate Constraint with Controllable Lead Times and Shared Cost Allocation. Operations Research Letters, 51(4), 385–392.
Christou, I. T., K. Skouri, and A. G. Lagodimos (2020). Fast Evaluation of a Periodic Review Inventory Policy. Computers and Industrial Engineering, 144, 106389.
Das, K. and S. Islam (2024). A Deterministic Multi-Item Inventory Model with Quadratic Demand under Neutrosophic and Pythagorean Hesitant Fuzzy Programming Approach. Results in Control and Optimization, 14, 100367.
De, S. K. (2021). Solving an EOQ Model under Fuzzy Reasoning. Applied Soft Computing, 99, 106892.
de Figueiredo, M. P. S., G. R. Moreira, C. C. R. de Brito, F. Gomes-Silva, A. L. Pinto dos Santos, M. L. L. da Costa, M. C. Filho, and L. Silva do Amaral (2023). Method to Generate Growth and Degrowth Models Obtained from Existing Models Compositions Applied to Animal Sciences – The Athens-Canadian Chicken Growth Case. Livestock Science, 269, 105162.
Dewi, D. C., E. R. EW, and S. Suganda (2019). Planning and Controlling Liquid Aluminum Sulfate Inventory with the EOQ Method Case Study at PDAM Tirta Mayang Jambi City. Journal of Science and Technology, 2, 121.
Dolgan, N. C., L. M. Haidar, B. Esmer, and M. Y. Jaber (2020). Temporary Price Increase during Replenishment Lead Time. Applied Mathematical Modelling, 78, 217–231.
Fitria, D., M. Pamuji, and M. Pompa (2015). Pump Motor Inverter at PDAM Tirta Musi Palembang. Journal of Technology Dissemination, 3(1), 46–55.
Gutierrez, M. and F. A. Rivera (2021). Undershoot and Order Quantity Probability Distributions in Periodic Review, Reorder Point, Order-Up-to-Level Inventory Systems with Continuous Demand. Applied Mathematical Modelling, 91, 791–814.
Hansen, O., S. Transchel, and H. Friedrich (2022). Replenishment Strategies for Lost Sales Inventory Systems of Perishables under Demand and Lead Time Uncertainty. European Journal of Operational Research, 308(2), 661–675.
Lesmono, D. and T. Limansyah (2017). A Multi Item Probabilistic Inventory Model. Journal of Physics: Conference Series, 893(1), 012024.
Lesmono, D. and T. Limansyah (2019). A Probabilistic Inventory Model with Deterioration Factor and Continuous Discount Function. AIP Conference Proceedings, 2192(1), 060013.
Ophokenshi, N. P., C. W. I. Emmanuel, and M. O. Sadik (2019). Analysis of an Inventory System for Items with Stochastic Demand and Time Dependent Three-Parameter Weibull Deterioration Function. Applied Mathematics, 10(9), 728–742.
Otsu, T. and G. Taniguchi (2020). Kolmogorov–Smirnov Type Test for Generated Variables. Economics Letters, 195, 109401.
Rojano, A. P., A. Andrea, M. P. Polanco, M. S. Jiménez, and L. D. Rosa (2020). An Optimization Approach for Inventory Costs in Probabilistic Inventory Models: A Case Study. Revista Chilena de Ingenieria, 28, 383–395.
Saha, C., D. K. Jana, and A. Duary (2023). Enhancing Production Inventory Management for Imperfect Items Using Fuzzy Optimization Strategies and Differential Evolution (DE) Algorithms. Franklin Open, 5, 100051.
Salas-Navarro, K., J. Acevedo-Chedid, G. M. Árquez, W. F. Florez, H. Ospina-Mateus, S. S. Sana, and L. E. Cárdenas-Barrón (2020). An EPQ Inventory Model Considering an Imperfect Production System with Probabilistic Demand and Collaborative Approach. Journal of Advances in Management Research, 17(2), 282–304.
Sayed, A. I. A. and S. S. R. Muhammad (2022). A Simulation Study on The Simulated Annealing Algorithm in Estimating The Parameters of Generalized Gamma Distribution. Science and Technology Indonesia, 7(1), 84–90.
Silitonga, R. Y. H., L. R. Kristiana, and T. A. Parley (2021). A Multi-Item Probabilistic Inventory Model that Considers Expiration Factor, All Unit Discount Policy and Warehouse Capacity Constraints. Journal of Industrial Engineering, 23(2), 139–148.
Silver, E., D. Pyke, and D. Thomas (2017). Inventory Management and Production Planning Scheduling. CRC Press, fourth edition.
Susanti, E., F. M. Puspita, S. S. Supadi, E. Yuliza, and A. F. Ramadhan (2023). Improve Fuzzy Inventory Model of Fractal Interpolation with Vertical Scaling Factor. Science and Technology Indonesia, 8, 654–659.
Sutoni, A. and D. H. Taufik (2019). Inventory Planning with Method Q and Method P for Probabilistic Demand on Chrysanthemum Seeds at PT Transplants Indonesia. International Journal of Innovation in Enterprise System, 3(01), 38–46.
Wan, G., Y. Cao, and S. Wang (2022). Evaluation of a Joint Replenishment Policy with Sales-Based Threshold and Stochastic Demand. Computers and Industrial Engineering, 172, 108525.
Wang, L. and H. Chen (2022). Optimization of a Stochastic Joint Replenishment Inventory System with Service Level Constraints. Computers and Operations Research, 148, 106001.
Zhang, J., L. Deng, H. Liu, and T. C. E. Cheng (2022). Which Strategy Is Better for Managing Multi-Product Demand Uncertainty: Inventory Substitution or Probabilistic Selling? European Journal of Operational Research, 302(1), 79–95.
Authors
Dwipurwani, O., Puspita, F. M., Supadi, S. S., & Yuliza, E. (2024). Probabilistic Multi-Item Inventory Model for Chemicals in Regional Drinking Water Company. Science and Technology Indonesia, 9(4), 1024–1032. https://doi.org/10.26554/sti.2024.9.4.1024-1032
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