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15 results

Boosting the Immune System

Conference Proceeding
McEwan, C., Hart, E., & Paechter, B. (2007)
Boosting the Immune System. In Artificial Immune Systems, 316-327. doi:10.1007/978-3-540-85072-4_28
Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or modelling biologically plausible...

Finding feasible timetables using group-based operators.

Journal Article
Lewis, R. M. R. & Paechter, B. (2007)
Finding feasible timetables using group-based operators. IEEE Transactions on Evolutionary Computation. 11, 397-413. doi:10.1109/TEVC.2006.885162. ISSN 1089-778X
This paper describes the applicability of the so-called "grouping genetic algorithm" to a well-known version of the university course timetabling problem. We note that there a...

A local search for the timetabling problem.

Conference Proceeding
Rossi-Doria, O., Blum, C., Knowles, J., Sampels, M., Socha, K., & Paechter, B. (2001)
A local search for the timetabling problem. In E. Burke, & P. Causmaecker (Eds.), Proceedings of the Conference on the Practice and Theory of Automated Timetabling (PATAT 2002), 124-127
This work is part of the Metaheuristic Network, a European Commission project that seeks to empirically compare the performance of various metaheuristics on different combinat...

A GA evolving instructions for a timetable builder.

Conference Proceeding
Blum, C., Correia, S., Dorigo, M., Paechter, B., Rossi-Doria, O., & Snoek, M. (2001)
A GA evolving instructions for a timetable builder. In E. Burke, & P. Causmaecker (Eds.), Proceedings of the Conference on the Practice and Theory of Automated Timetabling (PATAT 2002), 120-123
In this work we present a Genetic Algorithm for tackling timetabling problems. Our approach uses an indirect solution representation, which denotes a number of instructions fo...

Solving CSPs with evolutionary algorithms using self-adaptive constraint weights.

Conference Proceeding
Eiben, A. E., Jansen, B., Michalewicz, Z., & Paechter, B. (2000)
Solving CSPs with evolutionary algorithms using self-adaptive constraint weights. In D. Whitley (Ed.), GECCO-2000 : proceedings of the genetic and evolutionary computation conference, 128-134
This paper examines evolutionary algorithms (EAs) extended by various penalty-based approaches to solve constraint satisfaction problems (CSPs). In some approaches, the penalt...