Evolutionary Computation for Dynamic Optimisation in Network Environments








Evolutionary Computation (EC) encompasses many research areas, which applies ideas from nature (especially from biology) to solve optimisation and search problems. EC has been successfully applied to many real world scenarios, especially for difficult and challenging problems and those problems that are difficult to define precisely. This project aims to investigate EC methods for solving Dynamic Network Optimization Problems (DNOPs). We aim to gain insight and further our understanding of how different EC methods can be applied to DNOPs via empirical and theoretical studies. It is important to carry out this research at both theoretical and empirical levels, as one can feed into the other. We will work with industrial partners (e.g., Rail Safety and Standards Board, and Network Rail) who will validate our research and participate in our project. We can utilise their skills and expertise in producing the underlying theoretical models, which can then be validated on real-world data supplied by them. This project has great potentials to fundamentally change the way in which DNOPs are treated, both from a real-world point of view and from the point of view of advancing our theoretical understanding. We plan to develop a prototype system, in collaboration with our industrial partners, for our industrial partners.

This project is a collaborative project between De Montfort University and University of Birmingham, Rail Safety and Standards Board, and Network Rail. The total funding from EPSRC is £957,394 (£445,069 to De Montfort under Grant EP/K001310/1 and £512,325 to Birmingham under Grant EP/K001523/1). This project is for a duration of four years from 18 February 2013 to 17 February 2017.