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Government Led Tradable Truck Permit Optimisation Strategy for Multiterminal Ports to reduce emission in port area (Advert Reference: SF21/BL/MOS/LI)

   Faculty of Business and Law

  Dr Dongjun Li  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Port area congestion and the related emission are the growing problems worldwide (Schulte et al., 2017; Chen, Govindan and Golias, 2013). Truck Appoint Systems (TASs) have been applied at many marine container ports, especially at multiterminal ports and proven to be useful (Schulte et al., 2017). However, there is a lack of coordination between government and terminals, terminal and terminal, on how government issues the permits and how time slots are allocated to trucks across TASs. Reason for this is the permits are issued by the government and each terminal purchase permits from the government and operates its Truck Appointment System (TAS) independently. There is lack of information sharing and coordination mechanism between the stakeholders.

To improve such situation, this study will continue with the work conducted in our previous research which investigate the optimal contract design for the exchange of tradable truck permits (TTP) at multiterminal ports (Li et al., 2020).  The previous study designed a biliteral buy-back contract to coordinate the permits exchange in the terminals, one of the assumptions being made is that a fixed number of permits were available to the port. We will relax this assumption in this study.

The research questions to be answered in this study are:

1)how the government make decisions on the number of permits,

2)how the terminals determine the number of permits they should purchase,

3)how the terminals exchange the TTPs,

This study will also gain insight on how information sharing could help the government and the terminals to achieve coordination on how the permits can be issued by the government and purchased by the terminals.

We will develop a game theoretical framework to investigate the proposed research questions. In this framework, Government and the terminals are considered as a whole system. Centralised decision-making model, decentralised decision-making model would be developed and trading mechanism between the terminals would be designed. The outcome will allow the government to monitor the impact of the terminals operation on emission, also provide the terminal managers optimal solutions on permits management whenever they input the required information.

Our study will develop a user-friendly information system if time allowance allowed. It can provide a platform for the government and the terminals to work together. By applying this system, the government can monitor the effect of issuing truck permits, and the terminals can achieve their maximised profit, in the context of satisfying the permits constraints.   

The study will examine the literature in truck permit management, (Zhang, Zeng and Chen, 2013), emission management at port area (Chen, Govindan and Yang, 2013; Giuliano and Brien, 2007), port congestion management. We will explore a way to combine the optimisation with information management, using game theory to coordinate the government emission management and port operation, to enable the terminals obtain maximised profit while emission target is met. This study will not only contribute to the truck management practice in port area and help with emission reduction, but also contribute to the theory body of operation research, operation optimisation.

This project is supervised by Dr Dongjun Li

Eligibility and How to Apply:

Please note eligibility requirement:

·       Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.

·       Appropriate IELTS score, if required.

For further details of how to apply, entry requirements and the application form, see 

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. SF21/…) will not be considered.

Deadline for applications: Open

Start Date: March 2022 or October 2022

Northumbria University takes pride in, and values, the quality and diversity of our staff and students. We welcome applications from all members of the community.

Funding Notes

Please note this is a self-funded project and does not include tuition fees or stipend.

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