PORT HINTERLAND INTERMODAL NETWORK OPTIMISATION FOR SUSTAINABLE DEVELOPMENT --A CASE STUDY OF CHINA Paper code: L14 3 June 2013

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1 PORT HINTERLAND INTERMODAL NETWORK OPTIMISATION FOR SUSTAINABLE DEVELOPMENT --A CASE STUDY OF CHINA Paper code: L14 3 June 2013 Yimiao GU 1, Jasmine Siu Lee LAM 2 1 PhD Student, Division of Infrastructure System and Maritime Studies, School of Civil and Environmental Engineering, Nanyang Technological University,Singapore 2 Assistant Professor, Division of Infrastructure System and Maritime Studies, School of Civil and Environmental Engineering, Nanyang Technological University,Singapore

2 Research Background Today, the shipping industry is facing the sustainable development challenges like many other industries. Shipping lines need to venture inland transport to offer door-to-door services. They have environmental concerns to cut down carbon emissions. Hence, intermodal container transport is becoming more and more important.

3 Research Background A single COST objective optimisation no longer meets the reality requires. More and more customers want a faster delivery and thus the TIME factor needs to be considered simultaneously.

4 Research Objectives To narrow these research gaps, a novel optimisation model for the tactical planning of port hinterland container flows is developed. A case study on China s intermodal optimisation is used to test this model accordingly.

5 Illustration of Our Model

6 Model Development About the detailed model, please refer the conference paper (L14). There are 2 objectives and 16 constraints in this model. The two objectives are: Min cost and Min time. We handle the carbon footprint as a constraint in our model (emission restriction). We use Pareto Optimal method to analyze the trade-offs between these two objectives. We can solve the problem instances through commercial solver CPLEX 12.4.

7 Case Study We choose the Yangtze River s hinterland in Central China as a case study. It includes 6 provinces and 1 municipality (Shanghai Municipality) as hinterland scope. The case study involves 2 domestic seaports: Shanghai Port and Ningbo-Zhoushan Port. 25 foreign seaports are selected accordingly. From each province, five big cities are chosen as inland city nodes. Hence 30 inland city nodes in total. Based on the current infrastructures in China, 5 railroad dry ports in Suzhou, Hangzhou, Nanjing, Wuhan and Changsha and 3 barge ports in Suzhou, Nanjing and Wuhan are considered.

8 Case Study Some assumptions: (1) 80% empty containers imported from overseas to China, while 20% empty containers exported from China to overseas. (2) One truck carries 2 TEUs, one rail carries 100 TEUs, and one barge carries 500 TEUs. (3) Every selected inland city has a demand of 1,500 TEUs in the planning period and the demand characteristics follow a uniform distribution.

9 Case Study The main input data are given in the table below:

10 Case Study Main findings: (1) When Min cost is the only objective, barge transport mode is most favorable. When Min time is the only objective, trucking is the preferred transportation mode. When both Min cost and Min time, there is a trade-off for the choice of transportation modes.

11 Case Study Main findings: (2) We set the parameter G (carbon footprint restriction) with a sufficiently high value here (greater than 590 kg per TEU). If a customer wants to receive containers soonest in 11 days after cargo arrival at a domestic seaport, the transportation cost will be more than $2,050 per TEU. However, if the customer demands the lowest transportation cost of $1,750 per TEU, he will have to wait for around 14 days.

12 Case Study Sensitivity analysis in carbon footprint restrictions (1) Modelling results at Scenario I (G=530kg)

13 Case Study Sensitivity analysis in carbon footprint restrictions (2) Modelling results at Scenario II (G=560kg)

14 Case Study Sensitivity analysis in carbon footprint restrictions (3) Modelling results at Scenario III (G=590kg and above)

15 Case Study Dry port and barge port usage rate comparison

16 Policy Implications (1) Barging is most environmentally friendly and cost effective. Local governments should give first priority to develop barge ports if the geographical conditions allow. (2) In inland China where natural waterways are not available, local governments need to consider the development of railroad dry ports as a priority. (3) Unless transit time is a major concern, trucking should not be encouraged for long distance transport. Barge or railway intermodal transport provides opportunities to reduce the ratio of last-mile trucking mileage to the total transport mileage.

17 Future Research (1) The model presented will be extended to consider sailing speed and bunker consumption in sea leg. (2) It is necessary to incorporate stochastic features in the model. (3) It is also beneficial to run more experiments with the inclusion of more end-customer demand nodes. (4) For operational planning, we can extend our model to optimise the container routing of each origin-destination pair.

18 Thanks for your Time Q and A?

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