Smart logistics: distributed control of green crowdsourced parcel services

Seok Gi Lee, Yuncheol Kang, Vittaldas V. Prabhu

Research output: Contribution to journalArticle

13 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)1-13
Number of pages13
JournalInternational Journal of Production Research
DOIs
StateAccepted/In press - Jan 10 2016

Fingerprint

Logistics
Fuel consumption
Feedback control
Costs
Decision making
Scheduling
Carbon
Processing
Experiments
Integrated
Integrated approach
Experiment
Delivery services
Markov decision process
Revenue
Timeliness
Optimal policy
Inclusion
Just-in-time
Carbon emissions

Keywords

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

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Management Science and Operations Research
  • Strategy and Management

Cite this

Smart logistics : distributed control of green crowdsourced parcel services. / Lee, Seok Gi; Kang, Yuncheol; Prabhu, Vittaldas V.

In: International Journal of Production Research, 10.01.2016, p. 1-13.

Research output: Contribution to journalArticle

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