Solving stochastic ship fleet routing problems with inventory management using branch and price

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract / Description of output

This paper describes a stochastic ship routing problem with inventory
management. The problem involves finding a set of least cost routes for
a fleet of ships transporting a single commodity when the demand for the
commodity is uncertain. Storage at supply and consumption ports is limited
and inventory levels are monitored in the model. Consumer demands are at
a constant rate within each time period in the deterministic problem, and in
the stochastic problem, the demand rate for a period is not known until the
beginning of that period. The demand situation in each time period can be
described by a scenario tree with corresponding probabilities.
A decomposition formulation is given and it is solved using a Branch and
Price framework. A master problem (set partitioning with extra inventory
constraints) is built, and the subproblems, one for each ship, are solved
by stochastic dynamic programming and yeild the columns for the master
problem. Each column corresponds to one possible tree of actions for
one ship giving its schedule loading/unloading quantities for all demand
scenarios. Computational results are given showing that medium sized
problems can be solved successfully.
Original languageEnglish
Title of host publicationSpringer Optimization and Its Applications
Subtitle of host publication2016 Advances in Stochastic and Deterministic Global Optimization
EditorsPanos M. Pardalos, Anatoly Zhigljavsky, Julius Žilinskas
ISBN (Electronic)978-3-319-29975-4
ISBN (Print)978-3-319-29973-0
Publication statusPublished - 8 Apr 2011


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