Smart logistics: distributed control of green crowdsourced parcel services

Seokgi Lee; Yuncheol Kang; Vittaldas V. Prabhu

doi:10.1080/00207543.2015.1132856

Smart logistics: distributed control of green crowdsourced parcel services

Seokgi Lee, Yuncheol Kang, Vittaldas V. Prabhu

Division of Business Administration

Research output: Contribution to journal › Article › peer-review

49 Scopus citations

Abstract

This paper presents the development of an integrated decision-making framework for on-demand parcel delivery services that considers Just-In-Time delivery, fuel consumption and carbon emissions. Optimal policies based on the Markov decision process are established to allow for inclusion of parcel delivery requests. The framework’s integrated dynamic algorithm, based on a continuous variable feedback control, allows for unified processing of delivery requests and route scheduling. Computational experiments show that the integrated approach could increase revenue by 6.4% by reducing fuel and emission costs by 2.5%; however, the approach may incur more cost in terms of timeliness compared to a myopic approach.

Original language	English
Pages (from-to)	6956-6968
Number of pages	13
Journal	International Journal of Production Research
Volume	54
Issue number	23
DOIs	https://doi.org/10.1080/00207543.2015.1132856
State	Published - 1 Dec 2016

Bibliographical note

Publisher Copyright:
© 2016 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

Markov decision process
carbon emissions
fuel consumption
just-in-time
on-demand delivery service

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10.1080/00207543.2015.1132856

Cite this

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title = "Smart logistics: distributed control of green crowdsourced parcel services",

abstract = "This paper presents the development of an integrated decision-making framework for on-demand parcel delivery services that considers Just-In-Time delivery, fuel consumption and carbon emissions. Optimal policies based on the Markov decision process are established to allow for inclusion of parcel delivery requests. The framework{\textquoteright}s integrated dynamic algorithm, based on a continuous variable feedback control, allows for unified processing of delivery requests and route scheduling. Computational experiments show that the integrated approach could increase revenue by 6.4% by reducing fuel and emission costs by 2.5%; however, the approach may incur more cost in terms of timeliness compared to a myopic approach.",

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AB - This paper presents the development of an integrated decision-making framework for on-demand parcel delivery services that considers Just-In-Time delivery, fuel consumption and carbon emissions. Optimal policies based on the Markov decision process are established to allow for inclusion of parcel delivery requests. The framework’s integrated dynamic algorithm, based on a continuous variable feedback control, allows for unified processing of delivery requests and route scheduling. Computational experiments show that the integrated approach could increase revenue by 6.4% by reducing fuel and emission costs by 2.5%; however, the approach may incur more cost in terms of timeliness compared to a myopic approach.

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Smart logistics: distributed control of green crowdsourced parcel services

Abstract

Bibliographical note

Keywords

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