Target-guided algorithms for the container pre-marshalling problem

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

37 Scopus Citations
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Author(s)

  • Ning Wang
  • Bo Jin
  • Andrew Lim

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)67-77
Journal / PublicationOmega (United Kingdom)
Volume53
Online published24 Dec 2014
Publication statusPublished - Jun 2015

Abstract

The container pre-marshalling problem (CPMP) aims to rearrange containers in a bay with the least movement effort; thus, in the final layout, containers are piled according to a predetermined order. Previous researchers, without exception, assumed that all the stacks in a bay are functionally identical. Such a classical problem setting is reexamined in this paper. Moreover, a new problem, the CPMP with a dummy stack (CPMPDS) is proposed. At terminals with transfer lanes, a bay includes a row of ordinary stacks and a dummy stack. The dummy stack is actually the bay space that is reserved for trucks. Therefore, containers can be shipped out from the bay. During the pre-marshalling process, the dummy stack temporarily stores containers as an ordinary stack. However, the dummy stack must be emptied at the end of pre-marshalling. In this paper, target-guided algorithms are proposed to handle both the classical CPMP and new CPMPDS. All the proposed algorithms guarantee termination. Experimental results in terms of the CPMP show that the proposed algorithms surpass the state-of-the-art algorithm.

Research Area(s)

  • Container pre-marshalling problem, Dummy stack, Target-guided algorithm

Citation Format(s)

Target-guided algorithms for the container pre-marshalling problem. / Wang, Ning; Jin, Bo; Lim, Andrew.

In: Omega (United Kingdom), Vol. 53, 06.2015, p. 67-77.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review