Towards self-aware PerAda systems.
Hart, E., & Paechter, B. (2010)
Towards self-aware PerAda systems. In E. Hart, C. McEwan, J. Timmis, & A. Hone (Eds.), Artificial Immune Systems: 9th International Conference, ICARIS 2010 Proceedings, 314-216. https://doi.org/10.1007/978-3-642-14547-6_28
Pervasive Adaptation (PerAda) refers to massive-scale pervasive information and communication systems which are capable of autonomously adapting to highly dynamic and open tec...
Solving a real world routing problem using multiple evolutionary algorithms.
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Solving a real world routing problem using multiple evolutionary algorithms. In Parallel Problem Solving from Nature — PPSN VII. , (871-880). https://doi.org/10.1007/3-540-45712-7_84
This paper investigates the solving of a real world routing problem using evolutionary algorithms embedded within a Multi-agent system (MAS). An architecture for the MAS is pr...
The continuous equilibrium optimal network design problem: a genetic approach.
Cree, N. D., Maher, M., & Paechter, B. (1999)
The continuous equilibrium optimal network design problem: a genetic approach. In M. G. H. Bell (Ed.), Transportation Networks: Recent Methodological advances, 163-174
A genetic algorithm (GA) program for providing a solution to the Continuous Equilibrium Network Design Problem (NDP) is introduced following a general discussion of the networ...
Computing the State of Specknets: further analysis of an innate immune-inspired model.
Davoudani, D., Hart, E., & Paechter, B. (2008)
Computing the State of Specknets: further analysis of an innate immune-inspired model. In P. Bentley, D. Lee, & S. Jung (Eds.), Artificial Immune Systems, 7th International Conference, ICARIS 2008, Phuket, Thailand, August 2008, Proceedings, 95-106. https://doi.org/10.1007/978-3-540-85072-4
Specknets consist of hundreds of miniature devices, which are each capable of processing data and communicating wirelessly across short distances. Such networks, with their gr...
Evaluation of a genetic representation for outline shapes
Lapok, P., Lawson, A., & Paechter, B. (2017)
Evaluation of a genetic representation for outline shapes. In GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference Companion, (1419-1422). https://doi.org/10.1145/3067695.3082501
This work in progress focuses on the evaluation of a genetic representation for outline shapes for planar mechanical levers which addresses the first stage of the complex real...
Improving a lecture timetabling system for university wide use
Paechter, B., Rankin, B., & Cumming, A. (1998)
Improving a lecture timetabling system for university wide use. In Practice and Theory of Automated Timetabling II. , (156-165). https://doi.org/10.1007/BFb0055887
During the academic year 1996/97 the authors were commissioned by their institution to produce an automated timetabling system for use by all departments within the Faculty of...
An Immune-Inspired Approach to Speckled Computing
Davoudani, D., Hart, E., & Paechter, B. (2006)
An Immune-Inspired Approach to Speckled Computing. In L. de Castro, F. Von Zuben, & H. Knidel (Eds.), Artificial Immune Systems. ICARIS 2007, 288-299. doi:10.1007/978-3-540-73922-7_25
Speckled Computing offers a radically new concept in information technology that has the potential to revolutionise the way we communicate and exchange information. Specks — m...
Solving CSPs with evolutionary algorithms using self-adaptive constraint weights.
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...
Strengthening the Forward Variable Selection Stopping Criterion
Herrera, L. J., Rubio, G., Pomares, H., Paechter, B., Guillén, A., & Rojas, I. (2009)
Strengthening the Forward Variable Selection Stopping Criterion. In Artificial Neural Networks – ICANN 2009. , (215-224). https://doi.org/10.1007/978-3-642-04277-5_22
Given any modeling problem, variable selection is a preprocess step that selects the most relevant variables with respect to the output variable. Forward selection is the most...
Real-world applications of evolutionary computing
Cagnoni, S., Poli, R., Smith, G. D., Corne, D., Oates, M., Hart, E., …Fogarty, T. C. (2000)
Real-world applications of evolutionary computing. In Proceedings of EvoWorkshops 2000
This book constitutes the refereed proceedings of six workshops on evolutionary computation held concurrently as EvoWorkshops 2000 in Edinburgh, Scotland, UK, in April 2000.