poster

Poster: FooDNet: Optimized On Demand Take-out Food Delivery using Spatial Crowdsourcing

Authors:

Yan Liu,

Bin Guo,

He Du,

Zhiwen Yu,

Daqing Zhang,

Chao ChenAuthors Info & Claims

MobiCom '17: Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking

Pages 564 - 566

https://doi.org/10.1145/3117811.3131268

Published: 04 October 2017 Publication History

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Abstract

This paper builds a Food Delivery Network (FooDNet) that investigates the usage of urban taxis to support on demand take-out food delivery by leveraging spatial crowdsourcing. Unlike existing service sharing systems (e.g., ridesharing), the delivery of food in FooDNet is more time-sensitive and the optimization problem is more complex regarding high-efficiency, huge-number of delivery needs. In particular, we study the food delivery problem in association with the Opportunistic Online Takeout Ordering & Delivery service (O-OTOD). Specifically, the food is delivered incidentally by taxis when carrying passengers in the O-OTOD problem, and the optimization goal is to minimize the number of selected taxis to maintain a relative high incentive to the participated drivers. The two-stage method is proposed to solve the problem, consisting of the construction algorithm and the Large Neighborhood Search (LNS) algorithm. Preliminary experiments based on real-world taxi trajectory datasets verify that our proposed algorithms are effective and efficient.

References

[1]

Chao Chen, Daqing Zhang, Xiaojuan Ma, Bin Guo, Leye Wang, Yasha Wang, and Edwin Sha. 2017. Crowddeliver: planning city-wide package delivery paths leveraging the crowd of taxis. IEEE Transactions on Intelligent Transportation Systems 18, 6 (2017), 1478--1496.

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[2]

Aashwinikumar Devari. 2016. Crowdsourced last mile delivery using social network. Ph.D. Dissertation. State University of New York at Buffalo.

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[3]

Bin Guo, Yan Liu, Wenle Wu, Zhiwen Yu, and Qi Han. 2017. ActiveCrowd: A Framework for Optimized Multi-Task Allocation in Mobile Crowdsensing Systems. IEEE Transactions on Human-Machine Systems 47, 3 (2017), 392--403.

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[4]

Bin Guo, Zhu Wang, Zhiwen Yu, Yu Wang, Neil Yen, Runhe Huang, and Xingshe Zhou. 2015. Mobile Crowd Sensing and Computing: The Review of an Emerging Human-Powered Sensing Paradigm. ACM Computing Surveys 48, 1 (2015) 1--31.

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Jan Karel Lenstra and AHG Kan. 1981. Complexity of vehicle routing and scheduling problems. Networks 11, 2 (1981), 221--227.

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Wang EWang HYang YLiu W(2022)Truthful Incentive Mechanism for Budget-Constrained Online User Selection in Mobile CrowdsensingIEEE Transactions on Mobile Computing10.1109/TMC.2021.308392021:12(4642-4655)Online publication date: 1-Dec-2022
https://doi.org/10.1109/TMC.2021.3083920
Wang HYang YWang ELiu XWei JWu J(2022)Bilateral Privacy-Preserving Worker Selection in Spatial CrowdsourcingIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2022.3186023(1-14)Online publication date: 2022
https://doi.org/10.1109/TDSC.2022.3186023
Wang HWang EYang YWu JDressler F(2022)Privacy-Preserving Online Task Assignment in Spatial Crowdsourcing: A Graph-based ApproachIEEE INFOCOM 2022 - IEEE Conference on Computer Communications10.1109/INFOCOM48880.2022.9796827(570-579)Online publication date: 2-May-2022
https://doi.org/10.1109/INFOCOM48880.2022.9796827
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Poster: FooDNet: Optimized On Demand Take-out Food Delivery using Spatial Crowdsourcing

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FooDNet: Toward an Optimized Food Delivery Network Based on Spatial Crowdsourcing
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Published In

MobiCom '17: Proceedings of the 23rd Annual International Conference on Mobile Computing and Networking

October 2017

628 pages

ISBN:9781450349161

DOI:10.1145/3117811

General Chair:
Kobus Van der Merwe
University of Utah
,
Program Chairs:
Ben Greenstein
Google, USA
,
Kannan Srinivasan
Ohio State University, USA

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 October 2017

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National Natural Science Foundation of China
Seed Foundation of Innovation and Creation for Graduate Students in NWPU
National Basic Research Program of China

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MobiCom '17

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SIGMOBILE

MobiCom '17: The 23rd Annual International Conference on Mobile Computing and Networking

October 16 - 20, 2017

Utah, Snowbird, USA

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MobiCom '17 Paper Acceptance Rate 35 of 186 submissions, 19%;

Overall Acceptance Rate 440 of 2,972 submissions, 15%

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Wang EWang HYang YLiu W(2022)Truthful Incentive Mechanism for Budget-Constrained Online User Selection in Mobile CrowdsensingIEEE Transactions on Mobile Computing10.1109/TMC.2021.308392021:12(4642-4655)Online publication date: 1-Dec-2022
https://doi.org/10.1109/TMC.2021.3083920
Wang HYang YWang ELiu XWei JWu J(2022)Bilateral Privacy-Preserving Worker Selection in Spatial CrowdsourcingIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2022.3186023(1-14)Online publication date: 2022
https://doi.org/10.1109/TDSC.2022.3186023
Wang HWang EYang YWu JDressler F(2022)Privacy-Preserving Online Task Assignment in Spatial Crowdsourcing: A Graph-based ApproachIEEE INFOCOM 2022 - IEEE Conference on Computer Communications10.1109/INFOCOM48880.2022.9796827(570-579)Online publication date: 2-May-2022
https://doi.org/10.1109/INFOCOM48880.2022.9796827
Dai TFan X(2021)Multi-Stove Scheduling for Sustainable On-Demand Food DeliverySustainability10.3390/su13231313313:23(13133)Online publication date: 26-Nov-2021
https://doi.org/10.3390/su132313133
Gao XHuang HLiu CWu FChen G(2021)Quality Inference Based Task Assignment in Mobile CrowdsensingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.296593233:10(3410-3423)Online publication date: 1-Oct-2021
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Ferdianto FJuwitasary HSatria Dharma DVivien (2021)Development of Mobile Application for Pre Order Food and Beverage2021 International Conference on Information Management and Technology (ICIMTech)10.1109/ICIMTech53080.2021.9535046(177-182)Online publication date: 19-Aug-2021
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Yen LKamsin I(2021)Providing Runner Platform for Personal Shopper, Delivery Services and Queue Assistant for Urban Community2021 14th International Conference on Developments in eSystems Engineering (DeSE)10.1109/DeSE54285.2021.9719415(285-290)Online publication date: 7-Dec-2021
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Liu ZLi KZhou XZhu NGao YLi K(2021)Multi-Stage Complex Task Assignment in Spatial CrowdsourcingInformation Sciences10.1016/j.ins.2021.11.084Online publication date: Dec-2021
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Liu YGuo BChen CDu HYu ZZhang DMa H(2019)FooDNet: Toward an Optimized Food Delivery Network Based on Spatial CrowdsourcingIEEE Transactions on Mobile Computing10.1109/TMC.2018.286186418:6(1288-1301)Online publication date: 1-Jun-2019
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FooDNet: Toward an Optimized Food Delivery Network Based on Spatial Crowdsourcing

Willingness to Subscribe to a Meal Kit Delivery Service: A First Investigation on Its Generated Impact in Italy

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