Managing the number of container reshuffles using a shared stacking policy

A.H. Gharehgozli; Yugang Yu; M.B.M. Koster, de; J.T. Udding

Managing the number of container reshuffles using a shared stacking policy

A.H. Gharehgozli, Yugang Yu, M.B.M. Koster, de, J.T. Udding

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Reshuffling is one of the most costly operations at container yards for loading the containers onto thecontainerships since it increases the berthing time. In this paper, a shared stacking policy is proposed to stack the containers of multiple ships in one block of containers. A dynamic programming model is suggested to determine the exact storage positions of the export containers based on their retrieval times in order to minimize the expected number of reshufflings. Dynamic programming is not capable of solving realistically-sized problems in a reasonable time, so a heuristic algorithm is suggested. The main aim of the heuristic algorithm is to build decision trees whichcan be applied to solve large scale problems.

Original language	English
Title of host publication	Proceedings of the 2009 Conference on Value Chain Sustainability (ICOVACS 2009), 19-21 October 2009, Louisville, KY, U.S.A.
Place of Publication	United States, Louisville, KY
Pages	199-204
Publication status	Published - 2010

Cite this

@inproceedings{e171d58c7aa548d79fcb4ffc4a6661f0,

title = "Managing the number of container reshuffles using a shared stacking policy",

abstract = "Reshuffling is one of the most costly operations at container yards for loading the containers onto thecontainerships since it increases the berthing time. In this paper, a shared stacking policy is proposed to stack the containers of multiple ships in one block of containers. A dynamic programming model is suggested to determine the exact storage positions of the export containers based on their retrieval times in order to minimize the expected number of reshufflings. Dynamic programming is not capable of solving realistically-sized problems in a reasonable time, so a heuristic algorithm is suggested. The main aim of the heuristic algorithm is to build decision trees whichcan be applied to solve large scale problems.",

author = "A.H. Gharehgozli and Yugang Yu and {Koster, de}, M.B.M. and J.T. Udding",

year = "2010",

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booktitle = "Proceedings of the 2009 Conference on Value Chain Sustainability (ICOVACS 2009), 19-21 October 2009, Louisville, KY, U.S.A.",

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Managing the number of container reshuffles using a shared stacking policy. / Gharehgozli, A.H.; Yu, Yugang; Koster, de, M.B.M. et al.
Proceedings of the 2009 Conference on Value Chain Sustainability (ICOVACS 2009), 19-21 October 2009, Louisville, KY, U.S.A.. United States, Louisville, KY, 2010. p. 199-204.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Managing the number of container reshuffles using a shared stacking policy

AU - Gharehgozli, A.H.

AU - Yu, Yugang

AU - Koster, de, M.B.M.

AU - Udding, J.T.

PY - 2010

Y1 - 2010

N2 - Reshuffling is one of the most costly operations at container yards for loading the containers onto thecontainerships since it increases the berthing time. In this paper, a shared stacking policy is proposed to stack the containers of multiple ships in one block of containers. A dynamic programming model is suggested to determine the exact storage positions of the export containers based on their retrieval times in order to minimize the expected number of reshufflings. Dynamic programming is not capable of solving realistically-sized problems in a reasonable time, so a heuristic algorithm is suggested. The main aim of the heuristic algorithm is to build decision trees whichcan be applied to solve large scale problems.

AB - Reshuffling is one of the most costly operations at container yards for loading the containers onto thecontainerships since it increases the berthing time. In this paper, a shared stacking policy is proposed to stack the containers of multiple ships in one block of containers. A dynamic programming model is suggested to determine the exact storage positions of the export containers based on their retrieval times in order to minimize the expected number of reshufflings. Dynamic programming is not capable of solving realistically-sized problems in a reasonable time, so a heuristic algorithm is suggested. The main aim of the heuristic algorithm is to build decision trees whichcan be applied to solve large scale problems.

M3 - Conference contribution

SP - 199

EP - 204

BT - Proceedings of the 2009 Conference on Value Chain Sustainability (ICOVACS 2009), 19-21 October 2009, Louisville, KY, U.S.A.

CY - United States, Louisville, KY

ER -

Managing the number of container reshuffles using a shared stacking policy

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