Abstract
In recent years, many warehouses applied mobile robots to move products from one location to another. We focus on a traditional warehouse where agents are humans and they are engaged with tasks to navigate to the next destination one after the other. The possible destinations are determined at the beginning of the daily shift. Our real-world warehouse client asked us to minimise the total wage cost, and to minimise the irritation of the workers because of conflicts in their tasks. We extend Multi-Agent Path Finding (MAPF) solution techniques. We define a heuristic optimisation for the assignment of the packages. We have implemented our proposal in a simulation software and we have run several experiments. According to the experiments, the make-span and the wage cost cannot be reduced with the heuristic optimisation, however the heuristic optimisation considerably reduces the irritation of the workers. We conclude our work with a guideline for the warehouse.
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Acknowledgement
We thank K. Berczi for the optimisations from the real-world client. We thank A. Kiss for facilitating the initial programming work. The work of B. Ács, O. Jakab and L. Dóra was supported by the European Union, co-financed by the European Social Fund (EFOP-3.6.3-VEKOP-16-2017-00002). The work of L.Z. Varga was supported by the “Application Domain Specific Highly Reliable IT Solutions” project which has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the Thematic Excellence Programme TKP2020-NKA-06 (National Challenges Subprogramme) funding scheme.
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Ács, B., Dóra, L., Jakab, O., Varga, L.Z. (2021). Multi-agent Techniques to Solve a Real-World Warehouse Problem. In: Dignum, F., Corchado, J.M., De La Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection. PAAMS 2021. Lecture Notes in Computer Science(), vol 12946. Springer, Cham. https://doi.org/10.1007/978-3-030-85739-4_1
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