Abstract
We enhance the mobile sequential recommendation (MSR) model and address some critical issues in existing formulations by proposing three new forms of the MSR from a multi-user perspective. The multi-user MSR (MMSR) model searches optimal routes for multiple drivers at different locations while disallowing overlapping routes to be recommended. To enrich the properties of pick-up points in the problem formulation, we additionally consider the pick-up capacity as an important feature, leading to the following two modified forms of the MMSR: MMSR-m and MMSR-d. The MMSR-m sets a maximum pick-up capacity for all urban areas, while the MMSR-d allows the pick-up capacity to vary at different locations. We develop a parallel framework based on the simulated annealing to numerically solve the MMSR problem series. Also, a push-point method is introduced to improve our algorithms further for the MMSR-m and the MMSR-d, which can handle the route optimization in more practical ways. Our results on both real-world and synthetic data confirmed the superiority of our problem formulation and solutions under more demanding practical scenarios over several published benchmarks.
| Original language | English (US) |
|---|---|
| Article number | 3360048 |
| Journal | ACM Transactions on Knowledge Discovery from Data |
| Volume | 14 |
| Issue number | 5 |
| DOIs | |
| State | Published - Aug 2020 |
Keywords
- Mobile sequential recommendation
- parallel computing
- potential traveling distance
- simulated annealing
- trajectory data analysis
ASJC Scopus subject areas
- General Computer Science
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