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Article . 2018 . Peer-reviewed
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Article . 2018
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A flow‐first route‐next heuristic for liner shipping network design

Authors: Alexander Krogsgaard; David Pisinger; Jesper Thorsen;

A flow‐first route‐next heuristic for liner shipping network design

Abstract

Having a well‐designed liner shipping network is paramount to ensure competitive freight rates, adequate capacity on trade‐lanes, and reasonable transportation times. The most successful algorithms for liner shipping network design make use of a two‐phase approach, where they first design the routes of the vessels, and then flow the containers through the network in order to calculate how many of the customers’ demands can be satisfied, and what the imposed operational costs are. In this article, we reverse the approach by first flowing the containers through a relaxed network, and then design routes to match this flow. This gives a better initial solution than starting from scratch, and the relaxed network reflects the ideas behind a physical internet of having a distributed multi‐segment intermodal transport. Next, the initial solution is improved by use of a variable neighborhood search method, where six different operators are used to modify the network. Since each iteration of the local search method involves solving a very complex multi‐commodity flow problem to route the containers through the network, the flow problem is solved heuristically by use of a fast Lagrange heuristic. Although the Lagrange heuristic for flowing containers is 2–5% from the optimal solution, the solution quality is sufficiently good to guide the variable neighborhood search method in designing the network. Computational results are reported, showing that the developed heuristic is able to find improved solutions for large‐scale instances from LINER‐LIB, and it is the first heuristic to report results for the biggest WorldLarge instance.

Country
Denmark
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Keywords

Lagrange heuristic, Multi-commodity flow, Local search, Network design, Liner shipping

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Top 10%
Green
bronze