A decision support method for internal truck employment

Pages1378-1395
DOIhttps://doi.org/10.1108/IMDS-07-2014-0215
Publication Date07 Oct 2014
AuthorZ.X. Wang,Felix T.S. Chan,S.H. Chung,Ben Niu
SubjectInformation & knowledge management,Information systems,Data management systems
A decision support method for
internal truck employment
Z.X. Wang, Felix T.S. Chan and S.H. Chung
Department of Industrial and Systems Engineering,
The Hong Kong Polytechnic University, Hong Kong, Hong Kong, and
Ben Niu
College of Management, Shenzhen University, Shen Zhen,
China and Department of Industrial and Systems Engineering,
The Hong Kong Polytechnic University, Hong Kong, Hong Kong
Abstract
Purpose – The purpose of this paper is to propose a model that determines the strategy of owning
and renting trucks in combinations with internal truck scheduling and storage allocation problems in
container terminals.
Design/methodology/approach – To deal with this complicated problem, a two-level heuristic
approach is developed, in which the integration problem is decomposed into two levels. The first level
determines the daily operations of the internal trucks, while the second level determines the truck
employment strategy based on the calculation in the first level.
Findings – The results show that: even if the using cost of owned yard trucks is much lower than
the cost of rented yard tucks, terminal companies should not purchase too many trucks when the
purchasing price is high. In addition, the empirical truck employment strategies, which are pu rchasing
all the trucks or renting all the trucks, are not cost-effective when compared with the proposed yard
truck employment strategy.
Originality/value – The paper provides a novel insight for the internal truc k employment strategy
in container terminals which is the determination of the strategy of employing renting and outsourcing
yard trucks to meet operational daily transportation requirements and minimize the long-ter m cost
of employing yard trucks. A mathematical model is proposed to deal with the practical problem.
Also, this study presents better solution than empirical method for employing different types of
yard truck. Thus, in order to obtainmore benefit, terminal companies should employthe proposed yard
truck employment strategy.
Keywords Container terminal, Genetic algorithm, Storage allocation, Yard truck scheduling
Paper type Research paper
1. Introduction
From the first regular sea container service in 1961, container transshipments have
helped improve economic efficiency and cater for the rapidly growing market.
Nowadays, the ratio of transporting deep-sea general cargo by using containers to all
transportation means is over 60 percent (Steenken et al., 2004). The world container
throughput increased rapidly from 88 million twenty-foot equivalent units (TEUs) in
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0263-5577.htm
Industrial Management & Data
Systems
Vol. 114 No.9, 2014
pp. 1378-1395
rEmeraldGroup PublishingLimited
0263-5577
DOI 10.1108/IMDS-07-2014-0215
The authors would like to thank The Hong Kong Polytechnic University Research Committe e
(Project No.G-UB03) for financial and technical support, and also the Teaching Company Scheme
project (Project No. ZW1H (TCS162)), and a grant from The Hong Kong Scholars Program
Mainland – Hong Kong Joint Postdoctoral Fellows Program (Project No. G-YZ24), and The
National Natural Science Foundation of China (Grants Nos.71471158, 71271140), The authors
also would like to thank The Hong Kong Polytechnic University Research Committee for
financial and technical support.
1378
IMDS
114,9
1990 to 530 million TEUs in 2008, which corresponds to an increase of 500 percent, and
the container transshipment volume is still on long-term growth track (Tan and
Hilmola, 2012). Statistics show that the containeriz ed trade volumes increased by an
average of 7.8 percent from 2010 to 2012 around the world (United Nations, 2013). With
the increasing number of containers in marine transportation, more container
terminals, as well as container transporting equipment, such as quay cranes (QCs),
yard cranes and internal truc ks, are necessary for container operations. However, it is
difficult for some land-scarce regions in Asia to build more container terminals. Thus,
efficient management of container terminals, with better analysis and optimization to
improve productivity and container throughput, is needed more than ever before.
Therefore, this research is motivated by the increased importance of enhancin g the
efficiency in container terminals management.
Container throughput fluctuation always happens, not only in matu re port, such
as Hong Kong Port, as shown in Figure 1, but also in fast developing port, such as
Shanghai Port and Shenzhen Port. As demand fluctuation is common to terminal
industries, keeping a full fleet of truc ks to meet all the internal transpor tation
requirements is not economical (Petering, 2011). In addition, employing a large number
of trucks not only costs extra money, but may also result in traffic congestion
(Angeloudis and Bell, 2010). The study of the influence of container throughput
fluctuation during a period of time (e.g. one year) on yard truck employment strategies
is quite necessary for container terminal industry, since terminals companies should
decide the yard truck employment strategies based on the container throughout data.
A good way to overcome truck employment difficulties is to allow some internal trucks
to be rented from external companies, as has been done in the Hong Kong ter minals.
New decision problems appear when container terminals rent inter nal trucks since
the cost of owning and renting trucks are different. The first problem is to decide on the
number of trucks that should be owned, which is regarded as a long-term strategic
decision. This is because owning too many trucks requires heavy investment; also
renting additional trucks is not cheap. The other problem is how many truc ks should
be rented each day to meet the daily transportation requirement with a satisfactory
performance level. Both of these two problems are closely related to the productivity
1,100,000
1,150,000
1,200,000
1,250,000
1,300,000
1,350,000
1,400,000
1,450,000
1,500,000
1,550,000
1,600,000
123456789101112
(Month)
Container Throughput in TEU
Source: Port and Maritime Statistics of Marine Department of
Hong Kong (2014)
Figure 1.
Container Throughput
of Hong Kong Port in
the year 2012
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Internal truck
employment

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