Journal Screenshot

International Journal of Academic Research in Business and Social Sciences

Open Access Journal

ISSN: 2222-6990

Minimizing the Total Cost of Inventory by Using Artificial Bee Colony Algorithm

Nurul Syakira Mohd Zin, Siti Hafawati Jamaluddin, Norwaziah Mahmud, Nur Syuhada Muhammat Pazil

http://dx.doi.org/10.6007/IJARBSS/v11-i7/10334

Open access

Inventory denotes the assets and important resources utilised in an organisation or industry in which it offers various benefits for firm cash flow and persistent viability. If the production inventory of a company faces shortage or other problems such as greater operating cost due to interest payments on loan cash, the management will be in a critical situation, thereby leading to loss of customers and profits. This encourages organisations to implement inventory control, which aims for the lowest total cost of inventory, among others. Therefore, this study employed the Artificial Bee Colony (ABC) algorithm to ascertain the minimum total cost of inventory. The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. The resulting outcomes revealed a minimum total cost of inventory obtainable of RM45.38, with an optimal order quantity of 37 units.

Barwa, T. M. (2015). Inventory Control as an Effective Decision-Making Model and Implementations for Company ’ s Growth. 3(5), 465–472.
Chuka, C. E., Oguejiofor, N. J., & Sunday, A. C. (2016). Evaluation and Optimization of Inventory Control Systems in Small and Medium Scale Industries. 2(1), 1–13.
Hadidi, A., Azad, S. K., & Azad, S. K. (2019). Structural Optimization Using Artificial Bee Colony Algorithm Structural optimization using artificial bee colony algorithm. May 2014.
Guo, Y., Li, X., Tang, Y., & Li, J. (2017). Heuristic Artificial Bee Colony Algorithm for Uncovering Community in Complex Networks. 2017.
Lemke, S. W., & Lemke, S. (2015). Inventory Optimization in Manufacturing Organizations.
Samak-kulkarni, M. S. M., & Rajhans, N. R. (2013). Determination of Optimum Inventory Model for Minimizing Total Inventory Cost. 51(NUiCONE 2012).
Singh, S. R., & Kumar, T. (2015). Inventory Optimization in Efficient Supply Chain Management. March.
Sohail, N., & Sheikh, T. H. (2018). A study of inventory management system case study. Journal of Adv Research in Dynamical & Control System, 10(10), 1176-1190.Tanthatemee, T., & Phruksaphanrat, B. (2017). Fuzzy Inventory Control System for Uncertain Demand and Supply. March 2012.
Xu, Y., Fan, P., & Yuan, L. (2013). A Simple and Efficient Artificial Bee Colony Algorithm.

In-Text Citation: (Zin et al., 2021)
To Cite this Article: Zin, N. S. M., Jamaluddin, S. H., Mahmud, N., & Pazil, N. S. M. (2021). Minimizing the Total Cost of Inventory by Using Artificial Bee Colony Algorithm. International Journal of Academic Research in Business and Social Sciences, 11(7), 1147–1154.