Dynamic barge planning with stochastic container arrivals

Volkan Gumuskaya; Willem L. van Jaarsveld; Remco M. Dijkman; Paul W.P.J. Grefen; Albert W. Veenstra

doi:10.1016/j.tre.2020.102161

Dynamic barge planning with stochastic container arrivals

Volkan Gumuskaya (Corresponding author)
, Willem L. van Jaarsveld
, Remco M. Dijkman
, Paul W.P.J. Grefen
, Albert W. Veenstra

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

22 Citations (Scopus)

Abstract

Barge transport suffers from a high degree of uncertainty resulting from unreliable container arrivals (e.g. due to deep sea vessel delays), and dynamism that leads to limited information availability during planning. This paper studies the impact of uncertainty and dynamism using real data of an inland terminal. Our method consists of iterating weekly operations for one year to evaluate the long term performance. Each iteration involves solving a stochastic program for planning barge calls, and then simulating actual events. We show that uncertainty has an impact of up to 53% and dynamism up to 20% on total costs.

Original language	English
Article number	102161
Journal	Transportation Research. Part E: Logistics and Transportation Review
Volume	144
DOIs	https://doi.org/10.1016/j.tre.2020.102161
Publication status	Published - 1 Dec 2020

Funding

This work is part of the ISOLA project with project number 438-13-214, which is partly financed by the Dutch Research Council (NWO) .

Funders
Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Keywords

hinterland transport
uncertainty
stochastic program
multimodal transport
barge planning
Uncertainty
Multimodal transport
Barge planning
Hinterland transport
Stochastic program
Dynamism

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10.1016/j.tre.2020.102161

Cite this

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title = "Dynamic barge planning with stochastic container arrivals",

abstract = "Barge transport suffers from a high degree of uncertainty resulting from unreliable container arrivals (e.g. due to deep sea vessel delays), and dynamism that leads to limited information availability during planning. This paper studies the impact of uncertainty and dynamism using real data of an inland terminal. Our method consists of iterating weekly operations for one year to evaluate the long term performance. Each iteration involves solving a stochastic program for planning barge calls, and then simulating actual events. We show that uncertainty has an impact of up to 53\% and dynamism up to 20\% on total costs. ",

keywords = "hinterland transport, uncertainty, stochastic program, multimodal transport, barge planning, Uncertainty, Multimodal transport, Barge planning, Hinterland transport, Stochastic program, Dynamism",

author = "Volkan Gumuskaya and \{van Jaarsveld\}, \{Willem L.\} and Dijkman, \{Remco M.\} and Grefen, \{Paul W.P.J.\} and Veenstra, \{Albert W.\}",

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doi = "10.1016/j.tre.2020.102161",

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AU - Gumuskaya, Volkan

AU - van Jaarsveld, Willem L.

AU - Dijkman, Remco M.

AU - Grefen, Paul W.P.J.

AU - Veenstra, Albert W.

PY - 2020/12/1

Y1 - 2020/12/1

N2 - Barge transport suffers from a high degree of uncertainty resulting from unreliable container arrivals (e.g. due to deep sea vessel delays), and dynamism that leads to limited information availability during planning. This paper studies the impact of uncertainty and dynamism using real data of an inland terminal. Our method consists of iterating weekly operations for one year to evaluate the long term performance. Each iteration involves solving a stochastic program for planning barge calls, and then simulating actual events. We show that uncertainty has an impact of up to 53% and dynamism up to 20% on total costs.

AB - Barge transport suffers from a high degree of uncertainty resulting from unreliable container arrivals (e.g. due to deep sea vessel delays), and dynamism that leads to limited information availability during planning. This paper studies the impact of uncertainty and dynamism using real data of an inland terminal. Our method consists of iterating weekly operations for one year to evaluate the long term performance. Each iteration involves solving a stochastic program for planning barge calls, and then simulating actual events. We show that uncertainty has an impact of up to 53% and dynamism up to 20% on total costs.

KW - hinterland transport

KW - uncertainty

KW - stochastic program

KW - multimodal transport

KW - barge planning

KW - Uncertainty

KW - Multimodal transport

KW - Barge planning

KW - Hinterland transport

KW - Stochastic program

KW - Dynamism

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DO - 10.1016/j.tre.2020.102161

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VL - 144

JO - Transportation Research. Part E: Logistics and Transportation Review

JF - Transportation Research. Part E: Logistics and Transportation Review

M1 - 102161

ER -

Dynamic barge planning with stochastic container arrivals

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Keywords

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