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. ...
Post-publication timetabling.
Conference Proceeding
Cumming, A., Paechter, B., & Rankin, R. C. (2000)
Post-publication timetabling. In 3rd International Conference on the Practice And Theory of Automated Timetabling, PATAT 2000, (107-108
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...
Optimising an Evolutionary Algorithm for Scheduling
Conference Proceeding
Urquhart, N., Chisholm, K., & Paechter, B. (2000)
Optimising an Evolutionary Algorithm for Scheduling. In Real-World Applications of Evolutionary Computing: EvoWorkshops 2000. , (307-318
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. ...
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...
Two evolutionary approaches to cross-clustering problems.
Conference Proceeding
Luchian, H., Paechter, B., Radulescu, V., & Luchian, S. (1999)
Two evolutionary approaches to cross-clustering problems. In Proceedings of the 1999 Congress on Evolutionary Computation, (860-870). https://doi.org/10.1109/CEC.1999.782514
Cross-clustering asks for a Boolean matrix to
be brought to a quasi-canonical form. The problem has
many applications in image processing, circuit design,
archaeology, ecology...
The continuous equilibrium optimal network design problem: a genetic approach.
Conference Proceeding
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...
Improving a lecture timetabling system for university wide use
Conference Proceeding
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...
Timetabling the classes of an entire university with an evolutionary algorithm.
Conference Proceeding
Paechter, B., Rankin, B., Cumming, A., & Fogarty, T. C. (1998)
Timetabling the classes of an entire university with an evolutionary algorithm. In T. Beck, & M. Schoenauer (Eds.), Parallel Problem Solving from Nature - PPSN V. , (865-874). https://doi.org/10.1007/BFb0056928
This paper describes extensions to an evolutionary algorithm that timetables classes for an entire University. A new method of dealing with multi-objectives is described along...
Extensions to a memetic timetabling system.
Conference Proceeding
Paechter, B., Cumming, A., Norman, M. G., & Luchian, H. (1996)
Extensions to a memetic timetabling system. In R. Burke (Ed.), Practice and Theory of Automated Timetabling, 251-265. https://doi.org/10.1007/3-540-61794-9_64
This paper describes work in progress to increase the performance of a memetic timetabling system. The features looked at are two directed mutation operators, targeted mutatio...