Abstract
The efficiency of a maritime container terminal mainly depends on the process of handling containers, especially during the ships loading process. A good stowage planning facilitates these processes. This paper deals with the containership stowage problem, referred to as the Master Bay Plan Problem (MBPP). It is a NP-hard minimization problem whose goal is to find optimal plans for stowing containers into a containership with a low containership operation cost, subject to a set of structural and operational restrictions. For MBPP, data are not available for confidentiality reasons. The lack of a performance evaluation benchmark of solution algorithms for MBPP raises the need for a generation of instances. Due to this limitation, we present a generation scheme of instances for the MBPP, which is based random generation according on selected sets of parameters. The parameters are variable within certain ranges to characterize the vessel and containers; the ranges are real-life values taken from the literature. A constructive loading heuristic for stowing containers into a containership is proposed in this paper to have reference solutions. An instance set, its known-best solutions and the generator are available on-line.
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Cruz-Reyes, L., Hernández H., P., Melin, P., Fraire H., H.J., Mar O., J. (2013). Constructive Algorithm for a Benchmark in Ship Stowage Planning. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Recent Advances on Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33021-6_31
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DOI: https://doi.org/10.1007/978-3-642-33021-6_31
Publisher Name: Springer, Berlin, Heidelberg
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