The impact of incomplete vessel arrival information on container stacking

Abstract

Container stacking determines the incoming containers’ exact locations in a terminal storage yard which matters to the competitiveness of a port. The uncertain stacking or arrival sequence of containers caused by uncertain vessel arrival information brings some new challenges to container stacking. Based on the perspective of uncertainty, this article uses heuristic algorithms to evaluate the use of vessel arrival information to reduce the number of reshuffles, which differs from previous research mainly in the following three aspects: firstly, three different stacking principles i.e. the least reshuffle principle, lowest stack principle and nearest stack principle, are combined to create five new heuristics. Secondly, the incomplete information is divided into little, moderate and high levels and a variety of scenarios with different levels of vessel arrival information are generated to explore the effect of incomplete information on container stacking. Lastly, numerical experiments demonstrate that the results for complete information are presented to provide a lower bound reference. Moreover, the results obtained by different heuristics under different levels of vessel arrival information are closely related to factors like the bay scale, the bay utilisation rate and the number of containers.

Keywords:

• reshuffle
• incomplete vessel arrival information
• outbound container
• container stacking
• heuristic algorithm

Acknowledgments

This research was supported by the 2017 Founded Major Project of NSFC (71731006), and Ministry of Education (MOE) of China Project of Key Research Institute of Humanities and Social Sciences at Universities (17JZD020).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the 2017 Founded Major Project of NSFC [grant number 71731006], and Ministry of Education (MOE) of China Project of Key Research Institute of Humanities and Social Sciences at Universities [grant number 17JZD020].