Outputs (7)

Peer-to-peer networks for scalable grid landscapes in social agent simulations. (2005)
Presentation / Conference Contribution
Craenen, B. G. W., & Paechter, B. (2005). Peer-to-peer networks for scalable grid landscapes in social agent simulations. In Proceedings of the Artificial Intelligence and Social Behaviour Convention (AISB) 2005 (64-71)

Recently, peer-to-peer networks have been proposed as the underlying architecture of large scale distributed social agent simulations. A number of problems arise when grid landscapes are used to represent the landscape in these simulations, primarily... Read More about Peer-to-peer networks for scalable grid landscapes in social agent simulations..

Fine-tuning a Genetic Algorithm for the General Timetable Problem (2005)
Presentation / Conference Contribution
Luchian, H., Ungureanasu, C., Paechter, B., & Petriuc, M. (2005). Fine-tuning a Genetic Algorithm for the General Timetable Problem. In The Practice and Theory of Automated Timetabling I (435-442)

Application of the Grouping Genetic Algorithm to University Course Timetabling (2005)
Presentation / Conference Contribution
Lewis, R., Lewis, R. M. R., & Paechter, B. (2005, March). Application of the Grouping Genetic Algorithm to University Course Timetabling. Presented at 5th European Conference in Evolutionary Computation in Combinatorial Optimisation (EvoCop 2005), Lausann

University Course Timetabling-Problems (UCTPs) involve the allocation of resources (such as rooms and timeslots) to all the events of a university, satisfying a set of hard-constraints and, as much as possible, some soft constraints. Here we work wit... Read More about Application of the Grouping Genetic Algorithm to University Course Timetabling.

Parallelization of population-based multi-objective meta-heuristics: An empirical study (2005)
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 simultaneously optimize all the objectives. However, the majority of this kind of pro... Read More about Parallelization of population-based multi-objective meta-heuristics: An empirical study.

An Empirical Analysis of the Grouping Genetic Algorithm: The Timetabling Case. (2005)
Presentation / Conference Contribution
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 look at the effects that these can have on the algorithm with respect to b... Read More about An Empirical Analysis of the Grouping Genetic Algorithm: The Timetabling Case..

Maintaining Connectivity in a Scalable and Robust Distributed Environment (2005)
Presentation / Conference Contribution
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 Gr

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 balancing, parallel evolutionary computation, agent-based simulation and artific... Read More about Maintaining Connectivity in a Scalable and Robust Distributed Environment.

Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2. (2005)
Presentation / Conference Contribution
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 distribution networks. Despite the fact that pump scheduling problem involves sev... Read More about Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2..