Parallelization of population-based multi-objective meta-heuristics: An empirical study
Journal Article
Baños, R., Gil, C., Paechter, B., & Ortega, J. (2006)
Parallelization of population-based multi-objective meta-heuristics: An empirical study. Applied Mathematical Modelling, 30(7), 578-592. https://doi.org/10.1016/j.apm.2005.05.021
In single-objective optimization it is possible to find a global optimum, while in the multi-objective case no optimal solution is clearly defined, but several that simultaneo...
An Empirical Analysis of the Grouping Genetic Algorithm: The Timetabling Case.
Conference Proceeding
Lewis, R., & Paechter, B. (2005)
An Empirical Analysis of the Grouping Genetic Algorithm: The Timetabling Case. In 2005 IEEE Congress on Evolutionary Computation, 2856-2863. https://doi.org/10.1109/cec.2005.1555053
A grouping genetic algorithm (GGA) for the university course timetabling problem is outlined. We propose six different fitness functions, all sharing the same common goal, and...
Maintaining Connectivity in a Scalable and Robust Distributed Environment
Conference Proceeding
Jelasity, M., Preuss, M., van Steen, M., & Paechter, B. (2005)
Maintaining Connectivity in a Scalable and Robust Distributed Environment. In H. E. Bal, K. P. Lohr, & A. Reinfeld (Eds.), 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02), (389-394). https://doi.org/10.1109/CCGRID.2002.1017166
This paper describes a novel peer-to-peer (P2P) environment for running distributed Java applications on the Internet. The possible application areas include simple load balan...
Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2.
Conference Proceeding
Lopez-Ibanez, M., Devi Prasad, T., & Paechter, B. (2005)
Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2. https://doi.org/10.1109/CEC.2005.1554716
Significant operational cost and energy savings can be achieved by optimising the schedules of pumps, which pump water from source reservoirs to storage tanks, in water distri...
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 memetic algorithm for the university course timetabling.
Book
Rossi-Doria, O., & Paechter, B. (2003)
A memetic algorithm for the university course timetabling. In CO2004 Book of Abstracts, 56. Lancaster University
PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation
Journal Article
de Toro Negro, F., Ortega, J., Ros, E., Mota, S., Paechter, B. & Martin, J. M. (2003)
PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation. Parallel Computing. 30, 551-816. doi:10.1016/j.parco.2003.12.012. ISSN 0167-8191
This paper deals with the study of the cooperation between parallel processing and evolutionary computation to obtain efficient procedures for solving multiobjective optimisat...
A comparison of the performance of different metaheuristics on the timetabling problem.
Conference Proceeding
Rossi-Doria, O., Sampels, M., Birattari, M., Chiarandini, M., Dorigo, M., Gambardella, L. M., …Stutzle, T. (2003)
A comparison of the performance of different metaheuristics on the timetabling problem. In E. Burke, & P. Causmaecker (Eds.), Practice and Theory of AutomatedTimetabling IV, 329-351. https://doi.org/10.1007/978-3-540-45157-0_22
The main goal of this paper is to attempt an unbiased comparison of the performance of straightforward implementations of five different metaheuristics on a university course ...
Routing using evolutionary agents and proactive transitions.
Book
Urquhart, N. B., Ross, P., Paechter, B., & Chisholm, K. (2002)
Routing using evolutionary agents and proactive transitions. In Applications of Evolutionary Computing, 696-705. Springer-Verlag
The authors have previously introduced the concept of building a delivery network using an agent-based system. The delivery networks are built in response to a real-world prob...
Solving a real world routing problem using multiple evolutionary algorithms.
Conference Proceeding
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...