Improving street based routing using building block mutations.
Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Improving street based routing using building block mutations. In J. Gottlieb, E. Hart, & S. Cagnoni (Eds.), Applications of Evolutionary Computing: EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN Kinsale, Ireland, April 3–4, 2002 Proceedings. , (189-202). https://doi.org/10.1007/3-540-46004-7_33
Street based routing (SBR) is a real-world inspired routing problem that builds routes within an urban area for mail deliveries. The authors have previously attempted to solve...
Metaheuristics for university course timetabling.
Book Chapter
Lewis, R. M. R., Paechter, B., & Rossi-Doria, O. (2007)
Metaheuristics for university course timetabling. In K. Dahal, K. Chen Tan, & P. Cowling (Eds.), Evolutionary Scheduling, (237-272). Berlin / Heidelberg: Springer. https://doi.org/10.1007/978-3-540-48584-1_9
In this chapter we consider the NP-complete problem of university
course timetabling. We note that it is often difficult to gain a deep understanding
of these sorts of problem...
2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2019)
2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms. In H. Rodrigues, J. Herskovits, C. Mota Soares, A. Araújo, J. Guedes, J. Folgado, …J. Madeira (Eds.), EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization, (926-937). https://doi.org/10.1007/978-3-319-97773-7_80
In this paper, we investigate the ability of genetic representation methods to describe two-dimensional outline shapes, in order to use them in a generative design system. A s...
Strengthening the Forward Variable Selection Stopping Criterion
Conference Proceeding
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...
This pervasive day: creative Interactive methods for encouraging public engagement with FET research
Journal Article
Helgason, I., Bradley, J., Egan, C., Paechter, B., & Hart, E. (2011)
This pervasive day: creative Interactive methods for encouraging public engagement with FET research. Procedia Computer Science, 7, 207-208. https://doi.org/10.1016/j.procs.2011.09.028
This paper describes a case study of a programme of interactive public engagement activities presented by the PerAda Co-ordination Action project (FET Proactive Initiative on ...
Improving vehicle routing using a customer waiting time colony.
Conference Proceeding
Sa'adah, S., Ross, P., & Paechter, B. (2004)
Improving vehicle routing using a customer waiting time colony. In J. Gottlieb, & G. Raidl (Eds.), Evolutionary Computation in Combinatorial Optimization, 188-198. https://doi.org/10.1007/978-3-540-24652-7_19
In the vehicle routing problem with time windows (VRPTW), there are two main objectives. The primary objective is to reduce the number of vehicles, the secondary one is to min...
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...
Solving CSPs using self-adaptive constraint weights: how to prevent EAs from cheating
Conference Proceeding
Eiben, A. E., Jansen, B., Michalewicz, Z., & Paechter, B. (2000)
Solving CSPs using self-adaptive constraint weights: how to prevent EAs from cheating. In GECCO'00: Proceedings of the 2nd Annual Conference on Genetic and Evolutionary Computation. , (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...
Evolving planar mechanisms for the conceptual stage of mechanical design
Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2019)
Evolving planar mechanisms for the conceptual stage of mechanical design. In GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. , (383-384). https://doi.org/10.1145/3319619.3322006
This study presents a method to evolve planar mechanism prototypes using an evolutionary computing approach. Ultimately, the idea is to provide drafts for designers at the con...
Computing the State of Specknets: an immune-inspired approach.
Conference Proceeding
Davoudani, D., Hart, E., & Paechter, B. (2009)
Computing the State of Specknets: an immune-inspired approach. In Performance Evaluation of Computer and Telecommunication Systems, 2008. SPECTS 2008. International Symposium on, 52-59
Speckled Computing is an emerging technology based on the
deployment of thousands of minute semiconductor grains in
dense, wireless networks known as Specknets. Specknets coll...