Enhancing Supply Chain Efficiency: Implementation of Vendor Managed Inventory in Inventory Routing Problem
Abstract
This article explores the integration of Vendor Managed Inventory (VMI) into the framework of the Inventory Routing Problem (IRP) as a strategic approach to enhance supply chain efficiency. VMI involves suppliers taking an active role in managing customer inventory levels and fostering real-time communication and data sharing. The Inventory Routing Problem addresses the challenge of optimizing delivery routes while simultaneously managing inventory levels. The benefits of implementing VMI in IRP include improved demand forecasting, reduced stockouts and overstock situations, and optimized routing and transportation. The study applies a method that strategically integrates Vendor Managed Inventory (VMI) into the Inventory Routing Problem (IRP) framework, utilizing real-time data sharing and optimized routing algorithms to enhance supply chain efficiency. This approach is evaluated through research findings highlighting its benefits and implementation challenges. Thus, we discuss the potential advantages and challenges associated with this integration. While VMI in IRP offers substantial benefits, data security, cultural shifts, and IT system integration must be addressed for successful implementation. This article provides insights into the promising synergy between VMI and IRP, offering organizations a competitive edge in the dynamic supply chain management landscape.
Downloads
References
Akindote, O. J. (2023). Digital Era: Navigating VMI and Supply Chain for Sustainable Success. 33–39. https://doi.org/10.5121/csit.2023.130904 DOI: https://doi.org/10.5121/csit.2023.130904
Aloui, A., Hamani, N., & Delahoche, L. (2021). An integrated optimization approach using a collaborative strategy for sustainable cities freight transportation: A Case study. Sustainable Cities and Society, 75(August), 103331. https://doi.org/10.1016/j.scs.2021.103331 DOI: https://doi.org/10.1016/j.scs.2021.103331
Archetti, C., & Speranza, M. G. (2016). The inventory routing problem: The value of integration. International Transactions in Operational Research, 23(3), 393–407. https://doi.org/10.1111/itor.12226 DOI: https://doi.org/10.1111/itor.12226
Barbosa-Povoa, A. P., & Pinto, J. M. (2020). Process supply chains: Perspectives from academia and industry. Computers and Chemical Engineering, 132. https://doi.org/10.1016/j.compchemeng.2019.106606 DOI: https://doi.org/10.1016/j.compchemeng.2019.106606
Bardeji, S. F., Saghih, A. M. F., & Mirghaderi, S. H. (2022). Multi-Objective Inventory and Routing Model for a Multiproduct and Multi-Period Problem of Veterinary Drugs. International Journal of Industrial Engineering : Theory Applications and Practice, 29(4), 464–486. https://doi.org/10.23055/ijietap.2022.29.4.6711
Bell, W. J., Dalberto, L. M., Fisher, M. L., Green?eld, A. J., Jaikumar, R., Kedia, P., Mack, R. G., & Prutzman, P. J. (1983). Improving the distribution of industrial gases with an on-line computerized routing and schedulingoptimizer. Interfaces, 13, 4–23 DOI: https://doi.org/10.1287/inte.13.6.4
de Maio, A., & Laganà, D. (2020). The effectiveness of Vendor Managed Inventory in the last-mile delivery: An industrial application. Procedia Manufacturing, 42, 462–466. https://doi.org/10.1016/j.promfg.2020.02.047 DOI: https://doi.org/10.1016/j.promfg.2020.02.047
Guimarães, T., C. Coelho, L., M. Schenekemberg, C., & T. Scarpin, C. (2019). The two-echelon multi-depot inventory-routing problem. Computers and Operations Research, 101, 220–233. https://doi.org/10.1016/j.cor.2018.07.024 DOI: https://doi.org/10.1016/j.cor.2018.07.024
Harahap, A. Z. M. K., & Rahim, M. K. I. A. (2017). Deterministic inventory routing problem (DIRP): A literature review. International Journal of Supply Chain Management, 6(4), 284–288.
Huang, S. H., & Lin, P. C. (2010). A modified ant colony optimization algorithm for multi-item inventory routing problems with demand uncertainty. Transportation Research Part E: Logistics and Transportation Review, 46(5), 598–611. https://doi.org/10.1016/j.tre.2010.01.006 DOI: https://doi.org/10.1016/j.tre.2010.01.006
Ibrahim, N., Sobry, S. C., Ismail, N. Z. F., & Harahap, A. Z. M. K. (2023). Supply Chain Risks, Green Supply Chain Management Practices, and Organizational Performance: A Research Direction. Information Management and Business Review, 15(3(SI)), 429–438. https://doi.org/10.22610/imbr.v15i3(si).3499 DOI: https://doi.org/10.22610/imbr.v15i3(SI).3499
Jabir, E., Panicker, V. V., & Sridharan, R. (2015). Multi-objective Optimization Model for a Green Vehicle Routing Problem. Procedia - Social and Behavioral Sciences, 189, 33–39. https://doi.org/10.1016/j.sbspro.2015.03.189 DOI: https://doi.org/10.1016/j.sbspro.2015.03.189
Kamarul, M., Abdul, I., Iteng, R., & Ahmad, M. A. (2017). A Deterministic Inventory Routing Model for the Single-period Problems with Finite Time Horizon. 6(2), 196–201.
Kamarul, M., Abdul, I., Zhong, Y., Aghezzaf, E., & Aouam, T. (2014). Modeling and solving the multiperiod inventory-routing problem with stochastic stationary. 52(14), 4351–4363. DOI: https://doi.org/10.1080/00207543.2014.883470
Karimi, M., Khademi-Zare, H., Zare-Mehrjerdi, Y., & Bagher Fakhrzad, M. (2022). Optimizing service level, price, and inventory decisions for a supply chain with retailers’ competition and cooperation under the VMI strategy. RAIRO - Operations Research, 56(2), 1051–1078. https://doi.org/10.1051/ro/2022039 DOI: https://doi.org/10.1051/ro/2022039
Mohammad, R. (2019). Inventory routing problem under dynamic, uncertain, and green considerations Mohammad Rahimi To cite this version : HAL Id : tel-02001046 Mohammad RAHIMI Inventory Routing Problem under Dynamic, Uncertain and Green Considerations.
Panfilova, E., Dzenzeliuk, N., Domnina, O., Morgunova, N., & Zatsarinnaya, E. (2020). The impact of cost allocation on key decisions of supply chain participants. International Journal of Supply Chain Management, 9(1), 552–558.
Rahim, M. K. I. A., Nadarajan, S. S. R., & Ahmad, M. A. (2017). Solving the single-period inventory routing problem with the deterministic approach. Journal of Engineering Science and Technology, 12(Special Issue 4), 165–175.
Rodrigues, F., Agra, A., Christiansen, M., Hvattum, L. M., & Requejo, C. (2019). Comparing techniques for modeling uncertainty in a maritime inventory routing problem. European Journal of Operational Research, 277(3), 831–845. https://doi.org/10.1016/j.ejor.2019.03.015 DOI: https://doi.org/10.1016/j.ejor.2019.03.015
Rohmer, S. U. K., Claassen, G. D. H., & Laporte, G. (2019). A two-echelon inventory routing problem for perishable products. Computers and Operations Research, 107, 156–172. https://doi.org/10.1016/j.cor.2019.03.015 DOI: https://doi.org/10.1016/j.cor.2019.03.015
Schuster Puga, M., & Tancrez, J. S. (2017). A heuristic algorithm for solving large location–inventory problems with demand uncertainty. European Journal of Operational Research, 259(2), 413–423. https://doi.org/10.1016/j.ejor.2016.10.037 DOI: https://doi.org/10.1016/j.ejor.2016.10.037
Soysal, M., Koç, Ç., Çimen, M., & ?bi?, M. (2023). Managing returnable transport items in a vendor-managed inventory system. Socio-Economic Planning Sciences, 86(December 2022). https://doi.org/10.1016/j.seps.2022.101504 DOI: https://doi.org/10.1016/j.seps.2022.101504
Tirkolaee, E. B., Sadeghi, S., Mooseloo, F. M., Vandchali, H. R., & Aeini, S. (2021). Application of Machine Learning in Supply Chain Management: A Comprehensive Overview of the Main Areas. Mathematical Problems in Engineering, 2021(Ml). https://doi.org/10.1155/2021/1476043 DOI: https://doi.org/10.1155/2021/1476043
Upadhyay, V. V., Tewari, P. C., & Gupta, A. (2013). Evaluation of Vendor Managed Inventory Elements in Manufacturing Sector Using ANOVA Technique. X(2).
Yadollahi, E., Aghezzaf, E. H., Walraevens, J., & Raa, B. (2019). Inventory Routing Problem with Non-stationary Stochastic Demands. Proceedings of the International Conference on Informatics in Control, Automation and Robotics, 2(Icinco), 658–665. https://doi.org/10.5220/0007948506580665 DOI: https://doi.org/10.5220/0007948506580665
Zhong, Y., & Aghezzaf, E.-H. (2012). Modeling and Solving the Multi-Period Inventory Routing Problem With Constant Demand Rates. Optimization and Simulation, 1987.
Copyright (c) 2024 AFIF HARAHAP, Ahmad Suffian Mohd Zahari, Noor Malinjasari Ali, Rabiatul Adawiyah Ma'arof
This work is licensed under a Creative Commons Attribution 4.0 International License.
Author (s) should affirm that the material has not been published previously. It has not been submitted and it is not under consideration by any other journal. At the same time author (s) need to execute a publication permission agreement to assume the responsibility of the submitted content and any omissions and errors therein. After submission of revised paper in the light of suggestions of the reviewers, the editorial team edits and formats manuscripts to bring uniformity and standardization in published material.
This work will be licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) and under condition of the license, users are free to read, copy, remix, transform, redistribute, download, print, search or link to the full texts of articles and even build upon their work as long as they credit the author for the original work. Moreover, as per journal policy author (s) hold and retain copyrights without any restrictions.