@inproceedings{b1110f0a17be4915bb6e61d45eba6fad,
title = "Delivery Zones Partitioning ConsideringWorkload Balance Using Clustering Algorithm",
abstract = "This research proposes a novel approach for partitioning delivery zones in Bangkok that utilizes a combination of clustering and iterative algorithms. The approach leverages 30 days of delivery data to create delivery zones that having balanced workloads for drivers. The study begins by analyzing the delivery data to confirm the presence of unbalanced workloads across drivers within the 30-day period. To solve this imbalance, we use iterative k-means to adjust delivery zones considering the number of deliveries within the zone. The effectiveness of the approach was evaluated using two sets of parameters: geographic coordinates (latitude and longitude) and actual travel distance to reflect real-world scenarios. Regardless of the parameter set used, the experiments yielded balanced transportation areas with evenly distributed workloads. This approach demonstrates an improvement in workload equality compared to the original workload distribution.",
keywords = "K-Mean, Last Mile Logistics, Workload Balance, Zoning",
author = "Jaruwan Wangwattanakool and Wasakorn Laesanklang",
note = "Publisher Copyright: {\textcopyright} 2024 by SCITEPRESS – Science and Technology Publications, Lda.; 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2024 ; Conference date: 10-07-2024 Through 12-07-2024",
year = "2024",
doi = "10.5220/0012803800003758",
language = "English",
series = "Proceedings of the International Conference on Simulation and Modeling Methodologies, Technologies and Applications",
publisher = "Science and Technology Publications, Lda",
pages = "378--385",
editor = "{De Rango}, Floriano and Frank Werner and Gerd Wagner",
booktitle = "Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2024",
}