Ranking of Autonomous Alternatives for the Realization of Intralogistics using the TOPSIS Method

Authors

  • Kristina Raković Author

Abstract

The requirement for intralogistics activities to be automated has been impacted by current trends based on the impact of Industry 4.0, the growth of e-commerce, the emergence of the consumer society, therise in demand for logistics services, etc. Automatization of warehouseintralogistics is fundamental in aiming quickly responds to all userrequests. The most common intralogistics equipment in warehouses is theforklift. However, its engagement results in a low level of automation. Consequently, it is useful to implement autonomous technology, such as automatedguided vehicles (AGVs), automated mobile robots (AMRs), and drones,to have sustainable intralogistics activities. In addition to advantagesand limitations, their application in practice increases performance, adaptability, system efficiency,customer satisfaction, and accuracy and contributes tothe efficiency of the entire supply chain. The operating environment is morehumane,environmental standards are respected, and certain economic advantages are achieved. These technologies are compared using eightcriteria and the technique for order of preference by similarity to ideal solution (TOPSIS)method. AMR was selected as the most suitable option for implementing intralogistics activities. As the automation of intralogistics activities affects the entire supply chain, AMR is the solution that satisfies the social,environmental, and economic requirements of sustainable supply chain management.

Author Biography

  • Kristina Raković

    University of Belgrade, Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, 11000 Belgrade,Serbia

References

Ammar, M., Ahmed, M. M., & Abdullah, M. (2022). A Chain-Driven Live Roller Mechanism for Loading and Unloading

Packages on Autonomous Mobile Robots in Warehouses.Industrial Cognitive Ergonomics and Engineering Psychology, 35, 46.https://doi.org/10.5491/ahfe1001600.

Löffler, M., Boysen, N., & Schneider, M. (2023). Human-Robot Cooperation: Coordinating Autonomous Mobile

Robots and Human Order Pickers.Transportation Science, 57(4).https://doi.org/10.1287/trsc.2023.1207.

Szalanczi-Orban, V., & Vaczi, D. (2022). Use of Drones in Logistics Options in Inventory Control Systems.

Interdisciplinary Description of Complex Systems, 20(3), 295-303.https://doi.org/10.7906/indecs.20.3.9.

Maghazei, O., & Netland, T. (2020). Drones in manufacturing: Exploring opportunities for research andpractice.

Journal of Manufacturing Technology Management, 31(6), 1237-1259.https://doi.org/10.1108/JMTM-03-2019-0099.

Dabic-Miletic, S. (2023). Autonomous vehicles as anessential component of industry 4.0 for meeting last-mile

logistics requirements.Journal of Industrial Intelligence,1(1), 55-62.https://doi.org/10.56578/jii010104.

Bányai, T. (2023). Energy Efficiency of AGV-Drone Joint In-Plant Supply of Production Lines.Energies, 16(10), 4109.

https://doi.org/10.3390/en16104109.

Aydın, S., & Kahraman, C. (2014). Vehicle selectionfor public transportation using an integrated multi criteria

decision making approach: A case of Ankara.Journal of Intelligent & Fuzzy Systems, 26(5), 2467-2481.https://doi.org/10.3233/IFS-130917.

Plebani, M., Sciacovelli, L., Aita, A., Pelloso, M., & Chiozza, M. L. (2015). Performance criteria andquality indicators

Published

2026-07-21

How to Cite

(1)
Ranking of Autonomous Alternatives for the Realization of Intralogistics Using the TOPSIS Method. SEMS 2026, 1 (1), 48-57.