Abstract
The demand for package delivery services is extremely huge every day, because of the rapid development on online retailers. This leads to huge traffic congestion, resource consumption and environmental pollution (e.g. carbon emission). However, the urban public transport system offers a large amount of under-utilized capacity outside the peak hours. In this paper, we present the City-wide Package Distribution problem using Crowdsourced Public Transportation Systems (CPTS). That is, packages are delivered by carefully utilizing the considerable amount of idle capacity of the CPTS. Specifically, given a number of packages and the timetable of available CPTS trips, we optimize the package delivering scheme by determining the four identified states of any package at any time slot (waiting, riding, re-waiting and being unloaded). The delivering scheme can be modeled as an instance of the multi-commodity flow problem, and formulated by the Mixed Integer LinearProgramming techniques. We then propose an efficient heuristic solution for this NP-hard problem. Finally, our work is validated via comprehensive emulations with a real bus transportation network.
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