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Title: Integrated storage space allocation and ship scheduling problem in bulk cargo terminals
Authors: Tang, Lixin
Sun, Defeng
Liu, Jiyin
Keywords: Benders decomposition
Integer programming
Valid inequality
Variable reduction tests
Heuristics
Issue Date: 2015
Publisher: © IIE. Published by Taylor & Francis
Citation: TANG, L., SUN, D. and LIU, J., 2015. Integrated storage space allocation and ship scheduling problem in bulk cargo terminals. IIE Transactions, 48 (5), pp. 428-439.
Abstract: This study is motivated by the practices of large iron and steel companies that have steady and heavy demands for bulk raw materials, such as iron ore, coal, limestone, etc. These materials are usually transported to a bulk cargo terminal by ships (or to a station by trains). Once unloaded, they are moved to and stored in a bulk material stockyard, waiting for retrieval for use in production. Efficient storage space allocation and ship scheduling are critical to achieving high space utilization, low material loss, and low transportation costs. In this article, we study the integrated storage space allocation and ship scheduling problem in the bulk cargo terminal. Our problem is different from other associated problems due to the special way that the materials are transported and stored. A novel mixed-integer programming model is developed and then solved using a Benders decomposition algorithm, which is enhanced by the use of various valid inequalities, combinatorial Benders cuts, variable reduction tests, and an iterative heuristic procedure. Computational results indicate that the proposed solution method is much more efficient than the standard solution software CPLEX.
Description: This is an Accepted Manuscript of an article published by Taylor & Francis in IIE Transactions on 29 Jul 2015, available online: http://dx.doi.org/10.1080/0740817X.2015.1063791
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 the State Key Program of the National Natural Science Foundation of China (Grant No. 71032004)
Version: Accepted for publication
DOI: 10.1080/0740817X.2015.1063791
URI: https://dspace.lboro.ac.uk/2134/19971
Publisher Link: http://dx.doi.org/10.1080/0740817X.2015.1063791
ISSN: 0740-817X
Appears in Collections:Published Articles (Business School)

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