Scipediacontent: Scipediacontent moved page Draft Content 929931474 to Bao et al 2020a

2021-01-28T22:35:32Z

Scipediacontent moved page Draft Content 929931474 to Bao et al 2020a

Scipediacontent: Created page with " == Abstract == We investigate the problem of last-mile delivery, where a large amount of crowd-workers have performed a great quantity of location-specific urban logistics p..."

2021-01-28T22:35:28Z

Created page with " == Abstract == We investigate the problem of last-mile delivery, where a large amount of crowd-workers have performed a great quantity of location-specific urban logistics p..."

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== Abstract ==

We investigate the problem of last-mile delivery, where a large amount of crowd-workers have performed a great quantity of location-specific urban logistics parcels. Current existing approaches mainly focus on offline scenarios, where all the spatial-temporal information of parcels and workers are given. However, the offline scenarios can be impractical since parcels and workers appear dynamically in reality, and the information of workers is unknown in advance. In this paper, we study the problem of last-mile delivery on online scenarios to resolve the shortcomings of the offline setting. We first formalize the online parcel allocation in last-mile delivery problem, where all parcels were put in pop-stations in advance, and workers arrive dynamically. Then we propose a baseline algorithm with no competitive ratio, and an algorithm providing theoretical guarantee for the parcel allocation in last-mile delivery. Finally, we verify the effectiveness and efficiency of proposed algorithms through extensive experiments on real and synthetic datasets.

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/pdf/1806.05983 http://arxiv.org/pdf/1806.05983]

* [http://xplorestaging.ieee.org/ielx7/9039857/9050140/09050229.pdf?arnumber=9050229 http://xplorestaging.ieee.org/ielx7/9039857/9050140/09050229.pdf?arnumber=9050229],
: [http://dx.doi.org/10.1109/icmtma50254.2020.00194 http://dx.doi.org/10.1109/icmtma50254.2020.00194]

* [https://dblp.uni-trier.de/db/journals/corr/corr1806.html#abs-1806-05983 https://dblp.uni-trier.de/db/journals/corr/corr1806.html#abs-1806-05983],
: [https://arxiv.org/abs/1806.05983 https://arxiv.org/abs/1806.05983],
: [http://arxiv.org/pdf/1806.05983.pdf http://arxiv.org/pdf/1806.05983.pdf],
: [https://academic.microsoft.com/#/detail/3013634873 https://academic.microsoft.com/#/detail/3013634873]

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Bao et al 2020a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 929931474 to Bao et al 2020a

Scipediacontent: Created page with " == Abstract == We investigate the problem of last-mile delivery, where a large amount of crowd-workers have performed a great quantity of location-specific urban logistics p..."