Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/21674

Title: Modeling and solution for the ship stowage planning problem of coils in the steel industry
Authors: Tang, Lixin
Liu, Jiyin
Yang, Fei
Li, Feng
Li, Kun
Keywords: Stowage planning
Steel coils
Integer programming
Tabu search
Issue Date: 2015
Publisher: © Wiley
Citation: TANG, L. ...et al., 2015. Modeling and solution for the ship stowage planning problem of coils in the steel industry. Naval Research Logistics, 62(7), pp. 564-581.
Abstract: We consider a ship stowage planning problem where steel coils with known destination ports are to be loaded onto a ship. The coils are to be stowed on the ship in rows. Due to their heavy weight and cylindrical shape, coils can be stowed in at most two levels. Different from stowage problems in previous studies, in this problem there are no fixed positions on the ship for the coils due to their different sizes. At a destination port, if a coil to be unloaded is not at a top position, those blocking it need to be shuffled. In addition, the stability of ship has to be maintained after unloading at each destination port. The objective for the stowage planning problem is to minimize a combination of ship instability throughout the entire voyage, the shuffles needed for unloading at the destination ports, and the dispersion of coils to be unloaded at the same destination port. We formulate the problem as a novel mixed integer linear programming model. Several valid inequalities are derived to help reducing solution time. A tabu search (TS) algorithm is developed for the problem with the initial solution generated using a construction heuristic. To evaluate the proposed TS algorithm, numerical experiments are carried out on problem instances of three different scales by comparing it with a model-based decomposition heuristic, the classic TS algorithm, the particle swarm optimization algorithm, and the manual method used in practice. The results show that for small problems, the proposed algorithm can generate optimal solutions. For medium and large practical problems, the proposed algorithm outperforms other methods.
Description: This paper is in closed access until 22nd Oct 2016.
Sponsor: This research is partly supported by the Fund for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 71321001) and State Key Program of National Natural Science Foundation of China (Grant No. 71032004).
Version: Accepted for publication
DOI: 10.1002/nav.21664
URI: https://dspace.lboro.ac.uk/2134/21674
Publisher Link: http://dx.doi.org/10.1002/nav.21664
ISSN: 0894-069X
Appears in Collections:Closed Access (Business School)

Files associated with this item:

File Description SizeFormat
NRL-13-0142-acceepted.pdfAccepted version863.98 kBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.