Development of spreadsheet simulation models of gas cylinders inventory management
Abstract
The solution of the problem of managing the inventory of an enterprise whose activities are related to the purchase and sale of gas cylinders is considered. To solve the problem, it was necessary to investigate and choose the best inventory management strategy that provides the minimum value of the average inventory balance in the warehouse with the established upper limit of the average deficit. The problem of determining the best strategy is presented as a discrete programming problem, the required variables of which depend on the replenishment method. With a periodic replenishment strategy, the controlled variables are the volume of the delivery line and the delivery interval, with a threshold one, the minimum inventory level and the volume of the delivery line. Let’s also consider replenishment with a predicted inventory level, where the delivery level and the minimum inventory level are used as control variables. Three tabular simulation models with a given delivery time and random demand are proposed. Using the Chi-square test, it was found that the quantity demanded has a normal distribution law. By carrying out computational experiments, the optimal values of controlled variables were determined. The best objective function values were obtained using a model with a predicted inventory level and a threshold replenishment strategy. Experiments conducted on the basis of historical data have shown the advantage of the two model strategies compared to the strategy currently used in the enterprise. The use of a model with a predictable inventory level would reduce the average inventory balance by 46 %, and, consequently, save working capital. The results of the study can be useful for managers of enterprises whose activities are related to inventory management
Downloads
References
Khalilpourazari, S., Pasandideh, S. H. R. (2019). Modeling and optimization of multi-item multi-constrained EOQ model for growing items. Knowledge-Based Systems, 164, 150–162. doi: https://doi.org/10.1016/j.knosys.2018.10.032
Srivastava, H. M., Chung, K.-J., Liao, J.-J., Lin, S.-D., Lee, S.-F. (2020). An accurate and reliable mathematical analytic solution procedure for the EOQ model with non-instantaneous receipt under supplier credits. Revista de La Real Academia de Ciencias Exactas, Físicas y Naturales. Serie A. Matemáticas, 115 (1). doi: https://doi.org/10.1007/s13398-020-00944-x
Tavakoli, S., Taleizadeh, A. A. (2017). An EOQ model for decaying item with full advanced payment and conditional discount. Annals of Operations Research, 259 (1-2), 415–436. doi: https://doi.org/10.1007/s10479-017-2510-7
Dewi, S., Baihaqi, I., Widodo, E. (2015). Modeling Pooled Purchasing Strategy in Purchasing Consortium to Optimize Total Purchasing Cost. Procedia Manufacturing, 4, 478–486. doi: https://doi.org/10.1016/j.promfg.2015.11.065
Mitsel', A. A., Stavchuk, L. G. (2017). A three-product model to manage inventory with random demand. Economic analysis: theory and practice, 16 (3), 561–572. doi: https://doi.org/10.24891/ea.16.3.561
Gribanova, E. (2020). Development of iterative algorithms for solving the inverse problem using inverse calculations. Eastern-European Journal of Enterprise Technologies, 3 (4 (105)), 27–34. doi: https://doi.org/10.15587/1729-4061.2020.205048
Cui, L., Deng, J., Liu, F., Zhang, Y., Xu, M. (2017). Investigation of RFID investment in a single retailer two-supplier supply chain with random demand to decrease inventory inaccuracy. Journal of Cleaner Production, 142, 2028–2044. doi: https://doi.org/10.1016/j.jclepro.2016.11.081
Gutierrez, M., Rivera, F. A. (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. doi: https://doi.org/10.1016/j.apm.2020.09.014
Sadjadi, S. J., Makui, A., Dehghani, E., Pourmohammad, M. (2016). Applying queuing approach for a stochastic location-inventory problem with two different mean inventory considerations. Applied Mathematical Modelling, 40 (1), 578–596. doi: https://doi.org/10.1016/j.apm.2015.06.010
San-José, L. A., Sicilia, J., Abdul-Jalbar, B. (2021). Optimal policy for an inventory system with demand dependent on price, time and frequency of advertisement. Computers & Operations Research, 128, 105169. doi: https://doi.org/10.1016/j.cor.2020.105169
Pando, V., San-José, L. A., Sicilia, J., Alcaide-López-de-Pablo, D. (2021). Maximization of the return on inventory management expense in a system with price- and stock-dependent demand rate. Computers & Operations Research, 127, 105134. doi: https://doi.org/10.1016/j.cor.2020.105134
Abdul Halim, M., Paul, A., Mahmoud, M., Alshahrani, B., Alazzawi, A. Y. M., Ismail, G. M. (2021). An overtime production inventory model for deteriorating items with nonlinear price and stock dependent demand. Alexandria Engineering Journal, 60 (3), 2779–2786. doi: https://doi.org/10.1016/j.aej.2021.01.019
Noppadon, S., Wipawee, T. (2019). Heuristics for a periodic-review policy in a two-echelon inventory problem with seasonal demand. Computers & Industrial Engineering, 133, 292–302. doi: https://doi.org/10.1016/j.cie.2019.05.017
Bikulov, D., Holovan, O., Oliynyk, O., Shupchynska, K., Markova, S., Chkan, A. et. al. (2020). Optimization of inventory management models with variable input parameters by perturbation methods. Eastern-European Journal of Enterprise Technologies, 3 (3 (105)), 6–15. doi: https://doi.org/10.15587/1729-4061.2020.204231
Chinello, E., Lee Herbert-Hansen, Z. N., Khalid, W. (2020). Assessment of the impact of inventory optimization drivers in a multi-echelon supply chain: Case of a toy manufacturer. Computers & Industrial Engineering, 141, 106232. doi: https://doi.org/10.1016/j.cie.2019.106232
Chu, Y., You, F., Wassick, J. M., Agarwal, A. (2015). Simulation-based optimization framework for multi-echelon inventory systems under uncertainty. Computers & Chemical Engineering, 73, 1–16. doi: https://doi.org/10.1016/j.compchemeng.2014.10.008
Dachyar, M., Yadrifil, Y., Fahreza, I. (2019). Inventory management design for a rapid disaster relief, towards internet of things (IOT) potential. EUREKA: Physics and Engineering, 6, 9–18. doi: https://doi.org/10.21303/2461-4262.2019.001079
Castro, P. M., Aguirre, A. M., Zeballos, L. J., Méndez, C. A. (2011). Hybrid Mathematical Programming Discrete-Event Simulation Approach for Large-Scale Scheduling Problems. Industrial & Engineering Chemistry Research, 50 (18), 10665–10680. doi: https://doi.org/10.1021/ie200841a
Boshkoska, B. M., Damij, T., Jelenc, F., Damij, N. (2015). Abdominal surgery process modeling framework for simulation using spreadsheets. Computer Methods and Programs in Biomedicine, 121 (1), 1–13. doi: https://doi.org/10.1016/j.cmpb.2015.05.001
Gribanova, E. B., Logvin, I. N. (2020). Imitatsionnoe modelirovanie ekonomicheskikh protsessov. Praktikum v Excel. Moscow: KnoRus, 227. Available at: https://www.book.ru/book/936864
Bonilla-Enriquez, G., Caballero-Morales, S.-O. (2020). Simulation Model for Assessment of Non Deterministic Inventory Control Techniques. Asian Journal of Research in Computer Science, 5 (3), 63–70. doi: https://doi.org/10.9734/ajrcos/2020/v5i330144
Markova, N. A., Kioseva I. A. (2015). Imitatsiyne modeliuvannia upravlinnia zapasamy. Visnyk Berdianskoho universytetu menedzhmentu i biznesu, 2 (30), 50–56. Available at: http://nbuv.gov.ua/UJRN/vbumb_2015_2_12
Copyright (c) 2022 Ekaterina Gribanova, Artur Mitsel, Alexandr Shilnikov

This work is licensed under a Creative Commons Attribution 4.0 International License.
Our journal abides by the Creative Commons CC BY copyright rights and permissions for open access journals.
Authors, who are published in this journal, agree to the following conditions:
1. The authors reserve the right to authorship of the work and pass the first publication right of this work to the journal under the terms of a Creative Commons CC BY, which allows others to freely distribute the published research with the obligatory reference to the authors of the original work and the first publication of the work in this journal.
2. The authors have the right to conclude separate supplement agreements that relate to non-exclusive work distribution in the form in which it has been published by the journal (for example, to upload the work to the online storage of the journal or publish it as part of a monograph), provided that the reference to the first publication of the work in this journal is included.