An order control policy in crowdsourced parcel pickup and delivery service

Yuncheol Kang

doi:10.1007/978-3-319-99707-0_21

An order control policy in crowdsourced parcel pickup and delivery service

Yuncheol Kang

Division of Business Administration

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Crowdsourced parcel delivery service has progressed dramatically by actively incorporating innovative technologies and ideas. Yet, maximizing profitability of this new type of delivery service becomes another challenge for service providers as market grows. In this paper we study a service order control policy to maximize profitability from a service provider perspective. Specifically, we suggest an order admission control approach that determines acceptance or rejection of an incoming order according to its profitability characteristics. For this, we model the problem as an average reward Semi-Markov Decision Process and utilize reinforcement learning to obtain an optimal order control policy that maximizes overall profitability of a service provider. Through numerical illustrations, we show that our suggested approach outperforms traditional methods, especially when the order arrival rate is high. Thus, smart order management is an important component of parcel pickup and delivery services.

Original language	English
Title of host publication	Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings
Editors	Gyu M. Lee, Dimitris Kiritsis, Gregor von Cieminski, Ilkyeong Moon, Jinwoo Park
Publisher	Springer New York LLC
Pages	164-171
Number of pages	8
ISBN (Print)	9783319997063
DOIs	https://doi.org/10.1007/978-3-319-99707-0_21
State	Published - 2018
Event	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2018 - Seoul, Korea, Republic of Duration: 26 Aug 2018 → 30 Aug 2018

Publication series

Name	IFIP Advances in Information and Communication Technology
Volume	536
ISSN (Print)	1868-4238

Conference

Conference	IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2018
Country/Territory	Korea, Republic of
City	Seoul
Period	26/08/18 → 30/08/18

Bibliographical note

Publisher Copyright:
© 2018, IFIP International Federation for Information Processing.

Keywords

Admission control
Crowdsourced parcel delivery
Planning and decision-makings
Reinforcement learning
Smart logistics

Access to Document

10.1007/978-3-319-99707-0_21

Cite this

Kang, Y. (2018). An order control policy in crowdsourced parcel pickup and delivery service. In G. M. Lee, D. Kiritsis, G. von Cieminski, I. Moon, & J. Park (Eds.), Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings (pp. 164-171). (IFIP Advances in Information and Communication Technology; Vol. 536). Springer New York LLC. https://doi.org/10.1007/978-3-319-99707-0_21

Kang, Yuncheol. / An order control policy in crowdsourced parcel pickup and delivery service. Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings. editor / Gyu M. Lee ; Dimitris Kiritsis ; Gregor von Cieminski ; Ilkyeong Moon ; Jinwoo Park. Springer New York LLC, 2018. pp. 164-171 (IFIP Advances in Information and Communication Technology).

@inproceedings{a82f01df4373464ca8edbf59c99b51d6,

title = "An order control policy in crowdsourced parcel pickup and delivery service",

abstract = "Crowdsourced parcel delivery service has progressed dramatically by actively incorporating innovative technologies and ideas. Yet, maximizing profitability of this new type of delivery service becomes another challenge for service providers as market grows. In this paper we study a service order control policy to maximize profitability from a service provider perspective. Specifically, we suggest an order admission control approach that determines acceptance or rejection of an incoming order according to its profitability characteristics. For this, we model the problem as an average reward Semi-Markov Decision Process and utilize reinforcement learning to obtain an optimal order control policy that maximizes overall profitability of a service provider. Through numerical illustrations, we show that our suggested approach outperforms traditional methods, especially when the order arrival rate is high. Thus, smart order management is an important component of parcel pickup and delivery services.",

keywords = "Admission control, Crowdsourced parcel delivery, Planning and decision-makings, Reinforcement learning, Smart logistics",

author = "Yuncheol Kang",

note = "Publisher Copyright: {\textcopyright} 2018, IFIP International Federation for Information Processing.; IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2018 ; Conference date: 26-08-2018 Through 30-08-2018",

year = "2018",

doi = "10.1007/978-3-319-99707-0_21",

language = "English",

isbn = "9783319997063",

series = "IFIP Advances in Information and Communication Technology",

publisher = "Springer New York LLC",

pages = "164--171",

editor = "Lee, {Gyu M.} and Dimitris Kiritsis and {von Cieminski}, Gregor and Ilkyeong Moon and Jinwoo Park",

booktitle = "Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings",

}

Kang, Y 2018, An order control policy in crowdsourced parcel pickup and delivery service. in GM Lee, D Kiritsis, G von Cieminski, I Moon & J Park (eds), Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings. IFIP Advances in Information and Communication Technology, vol. 536, Springer New York LLC, pp. 164-171, IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2018, Seoul, Korea, Republic of, 26/08/18. https://doi.org/10.1007/978-3-319-99707-0_21

An order control policy in crowdsourced parcel pickup and delivery service. / Kang, Yuncheol.
Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings. ed. / Gyu M. Lee; Dimitris Kiritsis; Gregor von Cieminski; Ilkyeong Moon; Jinwoo Park. Springer New York LLC, 2018. p. 164-171 (IFIP Advances in Information and Communication Technology; Vol. 536).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An order control policy in crowdsourced parcel pickup and delivery service

AU - Kang, Yuncheol

PY - 2018

Y1 - 2018

N2 - Crowdsourced parcel delivery service has progressed dramatically by actively incorporating innovative technologies and ideas. Yet, maximizing profitability of this new type of delivery service becomes another challenge for service providers as market grows. In this paper we study a service order control policy to maximize profitability from a service provider perspective. Specifically, we suggest an order admission control approach that determines acceptance or rejection of an incoming order according to its profitability characteristics. For this, we model the problem as an average reward Semi-Markov Decision Process and utilize reinforcement learning to obtain an optimal order control policy that maximizes overall profitability of a service provider. Through numerical illustrations, we show that our suggested approach outperforms traditional methods, especially when the order arrival rate is high. Thus, smart order management is an important component of parcel pickup and delivery services.

AB - Crowdsourced parcel delivery service has progressed dramatically by actively incorporating innovative technologies and ideas. Yet, maximizing profitability of this new type of delivery service becomes another challenge for service providers as market grows. In this paper we study a service order control policy to maximize profitability from a service provider perspective. Specifically, we suggest an order admission control approach that determines acceptance or rejection of an incoming order according to its profitability characteristics. For this, we model the problem as an average reward Semi-Markov Decision Process and utilize reinforcement learning to obtain an optimal order control policy that maximizes overall profitability of a service provider. Through numerical illustrations, we show that our suggested approach outperforms traditional methods, especially when the order arrival rate is high. Thus, smart order management is an important component of parcel pickup and delivery services.

KW - Admission control

KW - Crowdsourced parcel delivery

KW - Planning and decision-makings

KW - Reinforcement learning

KW - Smart logistics

UR - http://www.scopus.com/inward/record.url?scp=85053265754&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-99707-0_21

DO - 10.1007/978-3-319-99707-0_21

M3 - Conference contribution

AN - SCOPUS:85053265754

SN - 9783319997063

T3 - IFIP Advances in Information and Communication Technology

SP - 164

EP - 171

BT - Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings

A2 - Lee, Gyu M.

A2 - Kiritsis, Dimitris

A2 - von Cieminski, Gregor

A2 - Moon, Ilkyeong

A2 - Park, Jinwoo

PB - Springer New York LLC

T2 - IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2018

Y2 - 26 August 2018 through 30 August 2018

ER -

Kang Y. An order control policy in crowdsourced parcel pickup and delivery service. In Lee GM, Kiritsis D, von Cieminski G, Moon I, Park J, editors, Advances in Production Management Systems. Smart Manufacturing for Industry 4.0 - IFIP WG 5.7 International Conference, APMS 2018, Proceedings. Springer New York LLC. 2018. p. 164-171. (IFIP Advances in Information and Communication Technology). doi: 10.1007/978-3-319-99707-0_21

An order control policy in crowdsourced parcel pickup and delivery service

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Fingerprint

Cite this