Integrated Container Fleet Management in Transportation Service Systems
Submitting Institution
Plymouth UniversityUnit of Assessment
Business and Management StudiesSummary Impact Type
EconomicResearch Subject Area(s)
Mathematical Sciences: Applied Mathematics
Information and Computing Sciences: Artificial Intelligence and Image Processing
Commerce, Management, Tourism and Services: Business and Management
Summary of the impact
The research outlined in this case study has led to (1) an understanding
of the complexities of shipping containerisation in the real world,
embracing container fleet sizing, container leasing, repositioning of
empty containers, ship scheduling, and shipping emissions; (2) innovative
concepts and approaches such as inventory-based threshold policies and
integrated container management; (3) development of a formal model and
associated decision-support tools for use in the management of containers
by key industry players - shipping companies and port authorities - in
collaboration with local academic partners. The research has been
translated into impact on shipping lines and container ports in several
countries.
Underpinning research
Containerisation is at the heart of the global logistics industry
responsible for the transport of goods around the world. Container
shipping itself is one of the fastest growing shipping industry sectors -
the annual growth rate in 1988-2008 was around 10% in container ship
fleets, container fleets, and container port throughput. Efficiency in the
logistics of the container supply-chain itself has become critical given
spiralling fuel costs, the scale of emissions from shipping, and, in
particular, the problem of empty containers. Over 90% of the UK imports
and exports are moved by containers, with at least one in every two
incoming containers leaving the UK empty. The cost of moving empty
containers around the globe exceeded US$16 billion in 2002. The problem
here is managing supply-chain logistics in the context of the realities of
dynamic operations, multiple uncertainties, global networks, severe
imbalance in the flow of goods between East & West, and the impact of
recession.
This has been the focus of research at Plymouth led by Professor
Dong-Ping Song who has been working on modelling and optimisation of
manufacturing and service logistics systems for two decades. From 2001 to
2004 he was a key member of the EPSRC/DfT funded research project
"Container World" at Imperial College, modelling the world container
shipping business. This was substantially developed in 2005-2012 with
members of the Plymouth University International Shipping & Logistics
Group.
Song has conducted a series of pioneering studies of container shipping.
He was among the first to propose new concepts, e.g. inventory-based
threshold control policies for empty container management, in which the
movement of empty containers is determined by the target inventory levels
at ports and on vessels (cf. Song, 2005, Optimal threshold control of
empty vehicle redistribution in two depot service systems, IEEE Trans.
On Automatic Control). Concepts were further developed to facilitate
easy-to-operate and near-to-optimal policies for repositioning empty
containers in dynamic stochastic situations. He also developed a decision-
support system for integrated container fleet management so that decisions
in different areas (e.g. in relation to fleet-sizing, leasing-in,
leasing-off, distributing, and repositioning) could be better coordinated.
Song's work combined analytical and simulation methods to establish and
evaluate the optimality of container management policies for complex
shipping systems. This has also resulted in a novel way of estimating CO2
emissions from container shipping which includes operational data -
exclusion of which led to flawed calculation of emissions. Song developed
new methods for, and provided insights to, robust container-ship
scheduling which minimized shipping emissions. The research has appeared
in 14 refereed journal articles, one book, one book chapter, 10 conference
articles, and 6 seminars to industries and international academics in the
period 2008-2012. Implementation in key installations, driven by the need
for efficiency, has informed and changed industry practice. Indeed a
recently published book by Song (2013) entitled Optimal Control and Optimization of Stochastic Supply Chain Systems
(Advances in Industrial Control) provides a ground breaking analysis
and assessment of containerisation that has been applauded by the industry
as a relevant and practical guide.
References to the research
Note: the underlined authors are Plymouth University staff. Dong was a
Post-Doctoral researcher at Plymouth at the time of the underlying
research. (With 2011 Journal Citation Report Impact Factor (IF) and 2010
ABS ranking).
1. Song, D.P. and Dong, J.X. (2012), Cargo routing and empty
container repositioning in multiple shipping service routes, Transportation
Research Part B: Methodological, 46(10): 1556-1575. (DOI:
10.1016/j.trb.2012.08.003) [IF = 2.856, ABS = 4*].
2. Qi, X.T. and Song, D.P. (2012), Minimising fuel emissions by
optimising vessel schedules in liner shipping with uncertain port times, Transportation
Research Part E: Logistics and Transportation Review, 48(4):
863-880. (DOI: 10.1016/j.tre.2012.02.001) [IF = 1.648; ABS = 3*]
3. Dong, J.X. and Song, D.P. (2012), Quantifying the impact of
inland transport time on container fleet sizing in a liner shipping
service with uncertainties, OR Spectrum, 34(1):155-180 (DOI:
10.1007/s00291-009-0185-4). [IF = 1.233; ABS = 3*]
4. Dong, J.X. and Song, D.P. (2009), Container fleet sizing and
empty repositioning in liner shipping systems, Transportation Research
Part E: Logistics and Transportation Review, 45(6):
860-877(DOI:10.1016/j.tre.2009.05.001). [IF = 1.648; ABS = 3*]
5. Song, D.P. and Earl, C.F. (2008), Optimal empty vehicle
repositioning and fleet-sizing for two-depot services systems, European
Journal of Operational Research, 185, 760- 777.
(DOI:10.1016/j.ejor.2006.12.034). [IF = 1.815; ABS = 3*]
6. Song, D.P. and Carter, J. (2008), Optimal empty vehicle
redistribution for hub-and- spoke transportation systems, Naval
Research Logistics, 55(2): 156-171. (DOI: 10.1002/nav.20274) [IF =
1.308; ABS = 3*]
Details of the impact
This section covers the impact of the research (1) on non-academic
communities through exploitation, by joint working with others, and (2) by
other institutes who have taken up the work (from publication or other
dissemination) and applied it without further direct Plymouth involvement.
Song was the international collaborator of the research grant awarded to
Prof. Qiushuang Chen at Nankai University in China ("Coordination
Mechanism and Cooperative Optimization and Scheduling in Green Container
Shipping Supply Chains", funded by National Science Foundation of
China). Song's research work on container fleet management and liner
shipping scheduling in the context of multiple uncertainties and ship
emissions has been further developed in the above project, and exploited
through application to the operations of industrial partners including
Tianjin Port, and the EAS International Shipping Cooperation. This has
helped industrial partners (1) improve their container inventory
management through better coordination and (2) improve their operational
activities by optimising and balancing multiple objectives (economic and
environmental performance) (cf. Source 1).
Song was invited as a visiting researcher at the Hong Kong University of
Science & Technology in April 2011 and led a research seminar: "CO2
emission from container shipping services". An outcome of the
collaboration between Professor Song and Professor Xiangtong Qi involved
the design of robust containership scheduling with uncertainty and
emission minimization. This has been explicitly exploited as a significant
part of the project, "Transforming Hong Kong's Ocean Container
Transport Logistics Network" (funded by the Research Grants Council
of Hong Kong), which emphasized local practical impact by providing
prototypes for the industry and managerial guidance for policy makers (cf.
Source 2).
Pusan National University independently took up Song's research on
container fleet management and empty container repositioning. This was the
basis of their work that was exploited by the Korean liner shipping
company, Hyundai Merchant Marine, and the software company, Softship Data
AG, Germany. The research has benefited both companies by providing them
with the tools for understanding and modelling resource utilization (cf.
Source 3).
Singapore National University took up Song's work on container shipping,
as the basis for collaboration with industrial partners. For example, the
project "Liner Shipping Network Design: Model Development, Algorithm
Design and Applications", used some of Song's results (e.g.
containership routing and scheduling, and empty container repositioning)
to change practice in the major Singapore-based shipping line, APL Co Pte
Ltd. (a unit of the multi-national Neptune Orient Lines, the 7th
largest container shipping company in the world). (cf. Source 4).
Sources to corroborate the impact
Because of the English-language difficulties of the Chinese business
users involved, we have obtained supporting statements from those
English-speaking academic collaborators who had the closest liaison with
the business users.
- Statement from Nankai University, China, on collaboration and
exploitation of research with Tianjin Port and the EAS International
Shipping Cooperation.
- Statement from Hong Kong University of Science and Technology, Hong
Kong, on collaboration and exploitation of research for the Hong Kong
Ocean Container Transport Logistics Network.
- Statement from Pusan National University, South Korea, on exploitation
of research with Hyundai Merchant Marine, Korea, and Softship Data,
Germany.
- Statement from Singapore National University, Singapore, on
exploitation of research with APL Co Pte Ltd.
- Research Councils UK (Gateway to Research) (2008) Establishing New
Collaborations with Academic and Industrial Communities http://gtr.rcuk.ac.uk/project/FFBA40B4-
F164-4320-A9AC-4D33DC642C8D