Optimising the Vehicle Ferry Loading

   School of Mathematics and Physics

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  Dr Xiang Song  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Applications are invited for a self-funded, 3-year full-time or 6-year part time PhD project.

The PhD will be based in the School of Mathematics and Physics, and will be supervised by Dr Xiang Song.

The work on this project could involve:

  • Analyse vehicle arrival data and generate scenarios with Monte Carlo simulation. 
  • Model the loading process as a two-stage stochastic optimization problem where the first stage involves the decisions about the yard policies and second stage considers the packing solution on the ferry with the objective of to reducing penalties incurred by failing to pack booked vehicles.
  • Design heurist/Meta-heuristic algorithms for the packing problems with realistic constraints from the ferry loading industry. 

Project description

At present a Vehicle Ferry Loading industry is considering the efficiency of loading cars, vans and lorries onto ferries. Although the “yard-men”, with years of experience, do this pretty well, by eye, they wondered what an optimal layout would look like, and thought about applying bin-packing algorithms to help find an optimal solution to the vehicle ferry loading problem. This problem could be NP-hard (computationally intensive) problem, and you don’t get the chance of picking any car from the queuing lanes in random order to complete the loading.

It leads to a study into how many more vehicles you could get onto a ferry, given knowledge of the vehicle lengths, and the order in which they were parked, to come up with as good a solution as possible. What if cars could be pre-sorted as they arrive? For example, the cars are routed into lanes in an order which could give a more efficient loading pattern. That might involve an ANPR camera on the approach road to the ferry terminal, and a lookup into the booking system to find the vehicle type and length, which they now have in place.

General admissions criteria

You'll need a good first degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Specific candidate requirements

Strong knowledge about Operational Research, esp. combinatorial optimization, heuristic and meta-heuristics algorithms. Previous programming experience with one of the following languages is needed c++, python and/or java. 

How to Apply

We encourage you to contact Dr Xiang Song ([Email Address Removed]) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Operational Research and Logistics PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code:SMAP7420423.

Mathematics (25)

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 About the Project