Container stacking and reshuffling are important issues in the management of operations in a container terminal. Minimizing the number of reshuffles can increase productivity of the yard cranes and the efficiency of the terminal. In this research, the authors improve the existing static reshuffling model, develop five effective heuristics, and analyze the performance of these algorithms. A discrete-event simulation model is developed to animate the stacking, retrieving, and reshuffling operations and to test the performance of the proposed heuristics and their extended versions in a dynamic environment with arrivals and retrievals of containers. The experimental results for the static problem show that the improved model can solve the reshuffling problem more quickly than the existing model and the proposed extended heuristics are superior to the existing ones. The experimental results for the dynamic problem show that the results of the extended versions of the five proposed heuristics are superior or similar to the best results of the existing heuristics and consume very little time.
Funding
This research was 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)
History
School
Business and Economics
Department
Business
Published in
IIE Transactions (Institute of Industrial Engineers)
Volume
47
Issue
7
Pages
751 - 766
Citation
YANG, L. ... et al., 2015. Research into container reshuffling and stacking problems in container terminal yards. IIE Transactions (Institute of Industrial Engineers), 47 (7), pp.751-766.
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Acceptance date
2014-09-16
Publication date
2015-02-25
Copyright date
2015
Notes
This is the peer reviewed version of the article, which has been published in final form at http://dx.doi.org/10.1080/0740817X.2014.971201. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.