Distributive Efficiency: Enhancing On-Time Delivery Through Accessibility and FIFO Integration

Authors

  • Atong Soekirman Trisakti Institute of Transportation and Logistics, Jakarta, Indonesia

DOI:

https://doi.org/10.38035/ijam.v3i1.527

Keywords:

Distribution System, Accessibility, FIFO, On time Delivery

Abstract

The purpose of this scientific article is to provide insight into strategies and steps that can be taken by companies to overcome such problems and improve the efficiency of their distribution systems. Thus, this article can contribute to the existing literature in the field of supply chain management, logistics, and overall business operations. The method used is qualitative by presenting the results in the literature derived from related scientific articles. Research findings are presented in the form of research reports or scientific articles that highlight the methodology, main findings, interpretation, and implications of the study. The final result of this scientific article makes a contribution from the perspective of the researcher. To achieve excellence in the distribution and delivery of goods, companies need to adopt a holistic approach and use the right technology. By taking into account findings from previous research, companies can improve their operational performance, reduce costs, and increase customer satisfaction through the implementation of efficient and innovative distribution strategies.

References

Abdolazimi, O. et al. (2020) ‘Robust design of a multi-objective closed-loop supply chain by integrating on-time delivery, cost, and environmental aspects, case study of a Tire Factory’, Journal of Cleaner Production, 264, p. 121566.

Ahmed, I. et al. (2023) ‘The nexus of energy in microgrids: A review on communication barriers in distributed networks auxiliary controls’, IET Generation, Transmission & Distribution, 17(22), pp. 4907–4922.

Arif, A.I. et al. (2018) ‘Power Distribution System Outage Management With Co-Optimization of Repairs, Reconfiguration, and DG Dispatch’, IEEE Transactions on Smart Grid, 9, pp. 4109–4118. Available at: https://api.semanticscholar.org/CorpusID:52121875.

Attar, H. et al. (2020) ‘Review and performance evaluation of FIFO, PQ, CQ, FQ, and WFQ algorithms in multimedia wireless sensor networks’, International Journal of Distributed Sensor Networks, 16(6), p. 1550147720913233.

Avila-Soler, E. et al. (2023) ‘Strategic location for the construction of a graphite trading warehouse in Mexico’, Journal of Applied Research and Technology [Preprint]. Available at: https://api.semanticscholar.org/CorpusID:257828062.

Baskar, S. and Palaniammal, S. (2014) ‘QUEUEING MODELS IN MOBILE AD-HOC NETWORKS’, American Journal of Applied Sciences, 11, pp. 308–315. Available at: https://api.semanticscholar.org/CorpusID:17623418.

Chopra, S. and Meindl, P. (2016) ‘Supply Chain Management–Strategy, Planning, and Operation 6 th Edition’.

Christopher, M. (2022) Logistics and supply chain management. Pearson Uk.

Coyle, J.J. et al. (2021) Supply chain management: a logistics perspective. Cengage Learning.

Das, S. et al. (2022) ‘FPGA Implementation of asynchronous FIFO’, in Proceedings of International Conference on Industrial Instrumentation and Control: ICI2C 2021. Springer, pp. 399–407.

Du, Z., Fan, Z.-P. and Chen, Z. (2023) ‘Implications of on-time delivery service with compensation for an online food delivery platform and a restaurant’, International Journal of Production Economics, 262, p. 108896.

ERD?L, A. (2021) ‘Development Supply Chain Management In Terms of Quality Function: An Application in the Manufacturing Industry’, Avrupa Bilim ve Teknoloji Dergisi, (26), pp. 456–465.

Garg, V. et al. (2023) ‘Drones in last-mile delivery: A systematic review on Efficiency, Accessibility, and Sustainability’, Transportation Research Part D: Transport and Environment, 123, p. 103831.

Hanum, B. (2022) ‘Analysis of Barcode System Design and Checklist to Reduce the Lead Time of Delivery of Goods using FIFO Method at PT Indofood TBK Company of Indonesia’, International Journal of Scientific and Academic Research (IJSAR), eISSN: 2583-0279, 2(6), pp. 1–8.

Heryanto, R.M. and Santoso, S. (2023) ‘Determination of Distribution Center Location using Analysis of Time-Based Set Covering Model and Maximal Covering Model Analysis’, OPSI [Preprint]. Available at: https://api.semanticscholar.org/CorpusID:259712092.

Hietasari, D.N., Subianto, D.I. and Adi, T.W. (2024) ‘Conceptual framework of warehouse management system with auto suggesting features for FIFO/FEFO implementation towards lean warehousing’, in AIP Conference Proceedings. AIP Publishing.

Holl, A. and Mariotti, I. (2018) ‘The geography of logistics firm location: the role of accessibility’, Networks and Spatial Economics, 18(2), pp. 337–361.

Hosseini, M.M. and Parvania, M. (2021) ‘Artificial intelligence for resilience enhancement of power distribution systems’, The Electricity Journal, 34(1), p. 106880.

Hugos, M.H. (2024) Essentials of supply chain management. John Wiley & Sons.

Karot, T. and Pornsing, C. (2024) ‘Just-in-Case Inventory Management under Partial Supply Disruptions’, The 11th Asia Conference on Mechanical and Materials Engineering (ACMME) [Preprint]. Available at: https://api.semanticscholar.org/CorpusID:266795164.

Kim, H.-C. and Nicholson, A.J. (2013) ‘Freight Transport Modal Shift in NZ: Building Understanding of Shippers’ Mode Choice based on RP (revealed preference)/ SP (stated preference) surveys’, in. Available at: https://api.semanticscholar.org/CorpusID:159216625.

Kostikov, E., Jílková, P. and Stránská, P.K. (2021) ‘Optimization of e-commerce distribution center location’, Marketing and Management of Innovations [Preprint]. Available at: https://api.semanticscholar.org/CorpusID:238041750.

Kukartsev, V. et al. (2023) ‘Using digital twins to create an inventory management system’, E3S Web of Conferences [Preprint]. Available at: https://api.semanticscholar.org/CorpusID:264111027.

Kula, E. et al. (2021) ‘Factors affecting on-time delivery in large-scale agile software development’, IEEE Transactions on Software Engineering, 48(9), pp. 3573–3592.

Kumar, A. (2021) ‘Improvement of public distribution system efficiency applying blockchain technology during pandemic outbreak (COVID-19)’, Journal of Humanitarian Logistics and Supply Chain Management, 11(1), pp. 1–28.

Laaksonen, H. et al. (2021) ‘Towards Flexible Distribution Systems: Future Adaptive Management Schemes’, Applied Sciences, 11, p. 3709. Available at: https://api.semanticscholar.org/CorpusID:234808701.

Luo, J., Rong, Y. and Zheng, H. (2020) ‘Impacts of logistics information on sales: Evidence from Alibaba’, Naval Research Logistics (NRL), 67, pp. 646–669. Available at: https://api.semanticscholar.org/CorpusID:212918735.

Mahdavi, M. et al. (2021) ‘Optimal Modeling of Load Variations in Distribution System Reconfiguration’, 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), pp. 1–6. Available at: https://api.semanticscholar.org/CorpusID:241606230.

Menaka, M. et al. (2023) ‘Asynchronous Circular Buffers based on FIFO for Network on Chips’, 2023 International Conference on Circuit Power and Computing Technologies (ICCPCT), pp. 1356–1361. Available at: https://api.semanticscholar.org/CorpusID:262131111.

Nurgaliev, I., Eskander, Y. and Lis, K. (2023) ‘The Use of Drones and Autonomous Vehicles in Logistics and Delivery’, Logistics and Transport [Preprint]. Available at: https://api.semanticscholar.org/CorpusID:258858091.

Orjuela-Castro, J.A., Orejuela-Cabrera, J.P. and Adarme-Jaimes, W. (2022) ‘Multi-objective model for perishable food logistics networks design considering availability and access’, OPSEARCH, 59(4), pp. 1244–1270.

Panchbhaiyye, V. and Ogunfunmi, T. (2021) ‘An efficient FIFO based accelerator for convolutional neural networks’, Journal of Signal Processing Systems, 93(10), pp. 1117–1129.

Primadianto, A. and Lu, C.-N. (2016) ‘A review on distribution system state estimation’, IEEE Transactions on Power Systems, 32(5), pp. 3875–3883.

Rahman, H.F. and Nielsen, I. (2019) ‘Scheduling automated transport vehicles for material distribution systems’, Applied Soft Computing, 82, p. 105552.

Ramadani, S.F., Bhawika, G.W. and Baihaqi, I. (2021) ‘Objective and Subjective Integration in Distribution Center Location Selection: A Case Study of Battery- electric Motorcycle Sales’, Proceedings of the 2nd International Conference on Business and Management of Technology (ICONBMT 2020) [Preprint]. Available at: https://api.semanticscholar.org/CorpusID:236602368.

Ren, S. et al. (2022) ‘Intelligent Manufacturing Planning System Using Dispatch Rules: A Case Study in Roofing Manufacturing Industry’, Applied Sciences [Preprint]. Available at: https://api.semanticscholar.org/CorpusID:250133344.

Rushton, A., Croucher, P. and Baker, P. (2022) The handbook of logistics and distribution management: Understanding the supply chain. Kogan Page Publishers.

Shestoperov, ?. and Rukavishnikova, T. (2016) ‘The Stabilization of the Regulatory Burden: The “One-In, One-Out” Principle Implementation Challenges’, in. Available at: https://api.semanticscholar.org/CorpusID:157538698.

Stevenson, W.J., Hojati, M. and Cao, J. (2018) COMM 225: Production & Operations Management: Custom Publication for Concordia University. McGraw-Hill Education Custom Publishing.

Tang, F. (2023) ‘Application of a Cold-Chain Logistics Distribution System Based on Cloud Computing and Web Delivery Date Management’, International Journal of Information Systems and Supply Chain Management (IJISSCM), 16(1), pp. 1–16.

Toubeau, J.-F. et al. (2020) ‘Data-driven scheduling of energy storage in day-ahead energy and reserve markets with probabilistic guarantees on real-time delivery’, IEEE Transactions on Power Systems, 36(4), pp. 2815–2828.

Verhetsel, A. et al. (2015) ‘Location of logistics companies: a stated preference study to disentangle the impact of accessibility’, Journal of transport geography, 42, pp. 110–121.

Waryanto, A. and Haryadi, R. (2024) ‘Application Of The Client Server Based Fifo Method In Raw Material Information Systems’, International Journal of Electrical Engineering, Mathematics and Computer Science, 1(1), pp. 16–21.

Wati, P.E.D.K. and Nuha, H. (2018) ‘Pengembangan Model Capacitated Maximal Covering Location Problem (CMCLP) Dalam Penentuan Lokasi Pendirian Gudang’, in. Available at: https://api.semanticscholar.org/CorpusID:169053275.

Yang, L. et al. (2022) ‘Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning’, Nature Machine Intelligence, 4, pp. 480–493. Available at: https://api.semanticscholar.org/CorpusID:248844096.

Zhou, G. et al. (2024) ‘Two-echelon time-dependent vehicle routing problem with simultaneous pickup and delivery and satellite synchronization’, Computers & Operations Research, p. 106600.

Zhu, Y., Chen, Y. and Fu, Z.-H. (2022) ‘Knowledge-guided two-stage memetic search for the pickup and delivery traveling salesman problem with FIFO loading’, Knowledge-Based Systems, 242, p. 108332.

Published

2024-06-28

How to Cite

Soekirman, A. (2024). Distributive Efficiency: Enhancing On-Time Delivery Through Accessibility and FIFO Integration . International Journal of Advanced Multidisciplinary, 3(1), 171–179. https://doi.org/10.38035/ijam.v3i1.527