Genetic algorithms and timetabling
Book Chapter
Ross, P., Hart, E., & Corne, D. (2003)
Genetic algorithms and timetabling. In A. Ghosh, & K. Tsutsui (Eds.), Advances in Evolutionary Optimisation. Springer. https://doi.org/10.1007/978-3-642-18965-4_30
Genetic algorithms can be used to search very large spaces, and it would seem natural to use them for tackling the nastier kinds of timetabling problem. We completed an EPSRC-...
Hyper Heuristics: an emerging direction in modern search technology.
Book Chapter
Burke, E., Hart, E., Kendall, G., Newall, J., Ross, P., & Schulenburg, S. (2003)
Hyper Heuristics: an emerging direction in modern search technology. In F. Glover, & G. A. Kochenberger (Eds.), Handbook of MetaHeuristics, 457-474. Springer US. https://doi.org/10.1007/0-306-48056-5_16
Requirements for getting a robot to grow-up
Conference Proceeding
Ross, P., Hart, E., Lawson, A., Webb, A., Prem, E., Poelz, P., & Morgavi, G. (2003)
Requirements for getting a robot to grow-up. In W. Banzhaf, T. Christaller, P. Dittrich, J. T. Kim, & J. Ziegler (Eds.), Advances in Artificial Life 7th European Conference, ECAL 2003, Dortmund, Germany, September 14-17, 2003. Proceedings. , (847-856). https://doi.org/10.1007/978-3-540-39432-7_91
Much of current robot research is about learning tasks in which the task to be achieved is pre-specified, a suitable technology for the task is chosen and the learning process...
Controlling a simulated Khepera with an XCS classifier system with memory.
Conference Proceeding
Webb, A., Hart, E., Ross, P. & Lawson, A. (2003)
Controlling a simulated Khepera with an XCS classifier system with memory. ISBN 9783540200574
Autonomous agents commonly suffer from perceptual aliasing in which differing situations are perceived as identical by the robots sensors, yet require different courses of act...
A systematic investigation of GA performance on jobshop scheduling problems.
Conference Proceeding
Hart, E., & Ross, P. (2003)
A systematic investigation of GA performance on jobshop scheduling problems. In Real-World Applications of Evolutionary Computing. , (280-289). https://doi.org/10.1007/3-540-45561-2_27
Although there has been a wealth of work reported in the literature on the application of genetic algorithms (GAs) to jobshop scheduling problems, much of it contains some gro...
Combining choices of heuristics.
Book
Ross, P., & Hart, E. (2001)
Combining choices of heuristics. In R. Sarker, M. Mohammadian, & X. Yao (Eds.), Evolutionary Optimization, 229-252. Kluwer
Exploiting the analogy between immunology and sparse distributed memory.
Conference Proceeding
Hart, E., & Ross, P. (2001)
Exploiting the analogy between immunology and sparse distributed memory. In J. Timmis, & P. J. Bentley (Eds.), ICARIS 2002 : 1st International Conference on Artificial Immune Systems, 59-67
The relationship between immunological memory and a class of associative memories known as sparse distributed memories (SDM) is well known. This paper proposes a new model for...
Clustering Moving Data with a Modified Immune Algorithm
Conference Proceeding
Hart, E., & Ross, P. (2001)
Clustering Moving Data with a Modified Immune Algorithm. In E. Boers (Ed.), Applications of Evolutionary Computing, 394-403. https://doi.org/10.1007/3-540-45365-2_41
In this paper we present a prototype of a new model for performing clustering in large, non-static databases. Although many machine learning algorithms for data clustering hav...
Enhancing the performance of a GA through visualisation.
Conference Proceeding
Hart, E., & Ross, P. (1999)
Enhancing the performance of a GA through visualisation. In Proceedings of GECCO-2000
This article describes a new tool for visualising genetic algorithms, (GAs) which is designed in order to allow the implicit mechanisms
of the GA | i.e. crossover and mutation...
Scheduling chicken catching - an investigation into the success of a genetic algorithm on a real world scheduling problem.
Journal Article
Hart, E., Ross, P., & Nelson, J. (1999)
Scheduling chicken catching - an investigation into the success of a genetic algorithm on a real world scheduling problem. Annals of Operations Research, 92, 363-380. https://doi.org/10.1023/A%3A1018951218434
Genetic Algorithms (GAs) are a class of evolutionary algorithms that have been successfully
applied to scheduling problems, in particular job-shop and flow-shop type problems
...