Abstract
This study focuses on the use of automated vehicles for last-mile delivery, specifically using local depots and integrated trucks-robots. The researchers developed two MILP models, RADP-1 and RADP-2, with RADP-2 being a modified version of TSP-D by [1]. The models were tested on three different service areas with varying customer densities, and it was found that robots were more efficient in areas with high customer densities. As the problem size increases, RADP-2 becomes more difficult to solve than RADP-1 due to the exponential increase in the number of feasible operations. The computational time of RADP-2 can be improved by removing operations that are unlikely to be part of the optimum solution.
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Jingi, A.M., Yang, X. (2023). Robot-Assisted Delivery Problems and Their Exact Solutions. In: Dorronsoro, B., Chicano, F., Danoy, G., Talbi, EG. (eds) Optimization and Learning. OLA 2023. Communications in Computer and Information Science, vol 1824. Springer, Cham. https://doi.org/10.1007/978-3-031-34020-8_26
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DOI: https://doi.org/10.1007/978-3-031-34020-8_26
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