Minimizing the risk of seaport operations efficiency reduction affected by vessel arrival delay
| Date | 13 August 2018 |
| DOI | https://doi.org/10.1108/IMDS-12-2017-0563 |
| Pages | 1498-1509 |
| Published date | 13 August 2018 |
| Author | Zhengxu Wang,Chonghui Guo |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
Minimizing the risk of seaport
operations efficiency reduction
affected by vessel arrival delay
Zhengxu Wang
School of Business Administration, Dongbei University of Finance and Economics,
Dalian, China and
Institute of Supply Chain Analytics, Dongbei University of Finance and Economics,
Dalian, China, and
Chonghui Guo
Institute of Systems Engineering, Dalian University of Technology, Dalian, China
Abstract
Purpose –In seaport industries, vessel arrival delay is inevitable because of numerous factors, e.g. weather,
delay due to the previous stop, etc. The period of delay can be as short at 15 min of as long as a few days. This
causes disruption to the planned sea operation operations, and more importantly, to the resources utilization.
In traditional berth allocation and quay crane assignment problems (BA-QCA), the risk of vessel arrival delay
has not been considered. Accordingly, the purpose of this paper is to employ a proactive planning approach
by taking into consideration the vessel arrival delay into the optimization of BA-QCA problems.
Design/methodology/approach –In the existing BA-QCA problems, vessel arrival time is usually
deterministic. In order to capture the uncertainties of arrival delay, this paper models the arrival time as a
probability distribution function. Moreover, this paper proposes to model the delay risk by using the period
between the expected arrival time and the expected waiting time of a vessel. Lastly, the authors propose a
new modified genetic algorithm and a new quay crane assignment heuristic to maximize the schedule
reliability of BA-QCA.
Findings –A number of numerical experiments are conducted. First of all, the optimization quality of the
proposed algorithm is compared with the traditional genetic algorithm for verifying the correctness of the
optimization approach. Then, the impact of vessel arrival delay is tested in different scenarios. The results
demonstrate that the impact of vessel arrival delay can be minimized, especially in the situations of high
vessel to potential berth ratio.
Research limitations/implications –The proposed vessel arrival modeling approach and the BA and
QCA approach can increase the operations efficiency of seaports. These approaches can increase the resource
utilization by reducing the effect of vessel arrival delay. In other words, this can improve the throughput of
seaport terminals.
Originality/value –This paper proposes to minimize the delay risk based on the conditional probability of
the vessel completion time based on the previous vessel at the assigned berth. This modeling approach is new
in literature.
Keywords Risk management, Berth allocation, Delay risk, Quay crane assignment, Seaport operations
Paper type Research paper
1. Introduction
Seaport is regarded as the interface between sea and inland transportations, mainly dealing
with the handling of import and export container operations, including loading and
unloading, and storages (Murty et al., 2005). Operations in a seaport are triggered by the
arrival of vessels. However, the planning of operations and resources allocation usually
starts a few weeks earlier than the actual arrival. When a vessel arrives at the seaport, it will
be assigned to a berth and wait for the service of quay cranes to unload and load of
containers (Steenken et al., 2004). Import containers will be transported to storage
temporarily at the yard by internal tractors, and wait for customers to pick-up. For export
containers, after the containers are brought in by external tractors, they will be stacked and
stored at the yard until the vessel for shipping them comes (Ng and Mak, 2006).
Industrial Management & Data
Systems
Vol. 118 No. 7, 2018
pp. 1498-1509
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-12-2017-0563
Received 7 December 2017
Revised 14 February 2018
Accepted 9 March 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
1498
IMDS
118,7
To continue reading
Request your trial