Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks
Journal Article
López-Ibáñez, M., Prasad, T. D., & Paechter, B. (2008)
Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks. Journal of Water Resources Planning and Management, 134, 337-346. https://doi.org/10.1061/%28ASCE%290733-9496%282008%29134%3A4%28337%29
Reducing energy consumption of water distribution networks has never had more significance than today. The greatest energy savings can be obtained by careful scheduling of ope...
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 tabu search evolutionary algorithm for solving constraint satisfaction problems.
Conference Proceeding
Craenen, B. G. W., & Paechter, B. (2006)
A tabu search evolutionary algorithm for solving constraint satisfaction problems. In Parallel Problem Solving from Nature - PPSN IX. , (152-161). https://doi.org/10.1007/11844297_16
The paper introduces a hybrid Tabu Search-Evolutionary Algorithm for solving the constraint satisfaction problem, called STLEA. Extensive experimental fine-tuning of parameter...
Solving a real world routing problem using evolutionary agents.
Conference Proceeding
Urquhart, N. B., Ross, P., Paechter, B. & Chisholm, K. (2002)
Solving a real world routing problem using evolutionary agents. ISBN 3540441395
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...
A framework for distributed evolutionary algorithms.
Conference Proceeding
Arenas, M. G., Collet, P., Eiben, A. E., Jeasity, M., Merelo Guervós, J. J., Paechter, B., …Schoenauer, M. (2002)
A framework for distributed evolutionary algorithms. In 7th International Conference, Granada, Spain, September 7-11, 2002, Proceedings, 665-675
This paper describes the recently released DREAM (Distributed Resource Evolutionary Algorithm Machine) framework for the automatic distribution of evolutionary algorithm (EA) ...
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...
Street-based routing using an evolutionary algorithm
Conference Proceeding
Urquhart, N. B., Paechter, B., & Chisholm, K. (2001)
Street-based routing using an evolutionary algorithm. In E. J. W. Boers, J. Gottlieb, P. L. Lanzi, R. E. Smith, S. Cagnoni, E. Hart, …H. Tijink (Eds.), Applications of Evolutionary Computing: EvoWorkshops 2001: EvoCOP, EvoFlight, EvoIASP, EvoLearn, and EvoSTIM, Proceedings. , (495-504). https://doi.org/10.1007/3-540-45365-2_51
Much research has been carried out into solving routing problems using both Evolutionary Techniques and other methods. In this paper the authors investigate the usage of an Ev...
Optimising an evolutionary algorithm for scheduling
Conference Proceeding
Urquhart, N. B., Chisholm, K., & Paechter, B. (2000)
Optimising an evolutionary algorithm for scheduling. In S. Cagnoni, R. Poli, G. D. Smith, D. Corne, M. Oates, E. Hart, …T. C. Fogarty (Eds.), Real-World Applications of Evolutionary Computing: EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight, Proceedings. , (307-318). https://doi.org/10.1007/3-540-45561-2_30
This paper examines two techniques for setting the parameters of an evolutionary Algorithm (EA). The example EA used for test purposes undertakes a simple scheduling problem. ...