Liner shipping service scheduling and cargo allocation

David Franz Koza*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Tactical service scheduling and operational cargo allocation are two interdependent problems in liner shipping. The schedules and sailing speeds of individual liner shipping services and the synchronization among all services determine the transit times of containers through a liner shipping network. On the other hand, the market demand in terms of container volume and expected transit times between origin and destination ports drive the schedule design of liner shipping services. We present a graph-based model and a branch-and-price algorithm to solve the combined problem. The goal is to minimize the difference between fuel consumption costs and revenues from transporting containers under consideration of transit time limits. Fuel consumption is modeled as a function of both speed and payload. Results are presented for 12 liner shipping networks and emphasize the importance of explicitly modeling schedules in large networks; transshipment times and thus transit times may be severely miscalculated otherwise. The results further show that neglecting payload in the fuel consumption function can result in suboptimal service schedules and cargo routing decisions.
Original languageEnglish
JournalEuropean Journal of Operational Research
Volume275
Issue number3
Pages (from-to)897-915
ISSN0377-2217
DOIs
Publication statusPublished - 2019

Keywords

  • Operations research in maritime industry
  • Liner shipping service scheduling
  • Cargo allocation and routing
  • Payload dependent fuel consumption
  • Branch and price

Cite this

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title = "Liner shipping service scheduling and cargo allocation",
abstract = "Tactical service scheduling and operational cargo allocation are two interdependent problems in liner shipping. The schedules and sailing speeds of individual liner shipping services and the synchronization among all services determine the transit times of containers through a liner shipping network. On the other hand, the market demand in terms of container volume and expected transit times between origin and destination ports drive the schedule design of liner shipping services. We present a graph-based model and a branch-and-price algorithm to solve the combined problem. The goal is to minimize the difference between fuel consumption costs and revenues from transporting containers under consideration of transit time limits. Fuel consumption is modeled as a function of both speed and payload. Results are presented for 12 liner shipping networks and emphasize the importance of explicitly modeling schedules in large networks; transshipment times and thus transit times may be severely miscalculated otherwise. The results further show that neglecting payload in the fuel consumption function can result in suboptimal service schedules and cargo routing decisions.",
keywords = "Operations research in maritime industry, Liner shipping service scheduling, Cargo allocation and routing, Payload dependent fuel consumption, Branch and price",
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Liner shipping service scheduling and cargo allocation. / Koza, David Franz.

In: European Journal of Operational Research, Vol. 275, No. 3, 2019, p. 897-915.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Liner shipping service scheduling and cargo allocation

AU - Koza, David Franz

PY - 2019

Y1 - 2019

N2 - Tactical service scheduling and operational cargo allocation are two interdependent problems in liner shipping. The schedules and sailing speeds of individual liner shipping services and the synchronization among all services determine the transit times of containers through a liner shipping network. On the other hand, the market demand in terms of container volume and expected transit times between origin and destination ports drive the schedule design of liner shipping services. We present a graph-based model and a branch-and-price algorithm to solve the combined problem. The goal is to minimize the difference between fuel consumption costs and revenues from transporting containers under consideration of transit time limits. Fuel consumption is modeled as a function of both speed and payload. Results are presented for 12 liner shipping networks and emphasize the importance of explicitly modeling schedules in large networks; transshipment times and thus transit times may be severely miscalculated otherwise. The results further show that neglecting payload in the fuel consumption function can result in suboptimal service schedules and cargo routing decisions.

AB - Tactical service scheduling and operational cargo allocation are two interdependent problems in liner shipping. The schedules and sailing speeds of individual liner shipping services and the synchronization among all services determine the transit times of containers through a liner shipping network. On the other hand, the market demand in terms of container volume and expected transit times between origin and destination ports drive the schedule design of liner shipping services. We present a graph-based model and a branch-and-price algorithm to solve the combined problem. The goal is to minimize the difference between fuel consumption costs and revenues from transporting containers under consideration of transit time limits. Fuel consumption is modeled as a function of both speed and payload. Results are presented for 12 liner shipping networks and emphasize the importance of explicitly modeling schedules in large networks; transshipment times and thus transit times may be severely miscalculated otherwise. The results further show that neglecting payload in the fuel consumption function can result in suboptimal service schedules and cargo routing decisions.

KW - Operations research in maritime industry

KW - Liner shipping service scheduling

KW - Cargo allocation and routing

KW - Payload dependent fuel consumption

KW - Branch and price

U2 - 10.1016/j.ejor.2018.12.011

DO - 10.1016/j.ejor.2018.12.011

M3 - Journal article

VL - 275

SP - 897

EP - 915

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 3

ER -