View : 85 Download: 0

Learning-based logistics planning and scheduling for crowdsourced parcel delivery

Title
Learning-based logistics planning and scheduling for crowdsourced parcel delivery
Authors
Kang, YuncheolLee, SeokgiChung, Byung Do
Ewha Authors
강윤철
Issue Date
2019
Journal Title
COMPUTERS & INDUSTRIAL ENGINEERING
ISSN
0360-8352JCR Link

1879-0550JCR Link
Citation
COMPUTERS & INDUSTRIAL ENGINEERING vol. 132, pp. 271 - 279
Keywords
Reinforcement learningCrowdsourced parcel deliveryAdmission controlContinuous feedback variable controlOn-demand delivery service
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Indexed
SCIE; SCOPUS WOS
Document Type
Article
Abstract
Today many domains have begun dealing with more complex and practical problems thanks to advances in artificial intelligence. In this paper, we study the crowdsourced parcel delivery problem, a new type of transportation, with consideration of complex and practical cases, such as multiple delivery vehicles, just-in-time (JIT) pickup and delivery, minimum fuel consumption, and maximum profitability. For this we suggest a learning-based logistics planning and scheduling (LIPS) algorithm that controls admission of order requests and schedules the routes of multiple vehicles altogether. For the admission control, we utilize reinforcement learning (RL) with a function approximation using an artificial neural network (ANN). Also, we use a continuous-variable feedback control algorithm to schedule routes that minimize both JIT penalty and fuel consumption. Computational experiments show that the LLPS outperforms other similar approaches by 32% on average in terms of average reward earned from each delivery order. In addition, the LLPS is even more advantageous when the rate of order arrivals is high and the number of vehicles that transport parcels is low.
DOI
10.1016/j.cie.2019.04.044
Appears in Collections:
경영대학 > 경영학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE