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Prof Ben Paechter's Outputs (93)

Revisiting the Central and Peripheral Immune System (2007)
Presentation / Conference Contribution
McEwan, C., Hart, E., & Paechter, B. (2007, August). Revisiting the Central and Peripheral Immune System. Presented at ICARIS 2007: International Conference on Artificial Immune Systems, Santos, Brazil

The idiotypic network has a long and chequered history in both theoretical immunology and Artificial Immune Systems. In terms of the latter, the drive for engineering applications has led to a diluted interpretation of the immunological models. Resea... Read More about Revisiting the Central and Peripheral Immune System.

An Immune-Inspired Approach to Speckled Computing (2007)
Presentation / Conference Contribution
Davoudani, D., Hart, E., & Paechter, B. (2007, August). An Immune-Inspired Approach to Speckled Computing. Presented at International Conference on Artificial Immune Systems ICARIS 2007, Beijing, China

Speckled Computing offers a radically new concept in information technology that has the potential to revolutionise the way we communicate and exchange information. Specks — minute, autonomous, semi-conductor grains that can sense and compute locally... Read More about An Immune-Inspired Approach to Speckled Computing.

Ensemble: embodied experiences in a sound and jewellery installation (2007)
Presentation / Conference Contribution
Kettley, S., Smyth, M., Arvind, D. K., Greig, F., McGregor, I., & Paechter, B. (2007, December). Ensemble: embodied experiences in a sound and jewellery installation. Presented at Create 07

ensemble - an interactive collection of networked jewellery with gesturally determined, real time sonic output

Solving optimal pump control problem using max-min ant system. (2007)
Presentation / Conference Contribution
Lopez-Ibanez, M., Prasad, T. D., & Paechter, B. (2007, July). Solving optimal pump control problem using max-min ant system. Presented at 9th Annual Genetic and Evolutionary Computation Conference (GECCO), London, UK

Finding feasible timetables using group-based operators. (2007)
Journal Article
Lewis, R. M. R., & Paechter, B. (2007). Finding feasible timetables using group-based operators. IEEE Transactions on Evolutionary Computation, 11, 397-413. https://doi.org/10.1109/TEVC.2006.885162

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 are, in fact, various scaling up issues surrounding this sort of algorithm a... Read More about Finding feasible timetables using group-based operators..

Metaheuristics for university course timetabling. (2007)
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). 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 problems due to the fact that so many different
types of constraints can ultima... Read More about Metaheuristics for university course timetabling..

Improving the Performance of Multi-objective Genetic Algorithm for Function Approximation Through Parallel Islands Specialisation (2006)
Presentation / Conference Contribution
Guillen, A., Rojas, I., Gonzalez, J., Pomares, H., Herrera, L. J., & Paechter, B. (2006, December). Improving the Performance of Multi-objective Genetic Algorithm for Function Approximation Through Parallel Islands Specialisation. Presented at 19th Australian Joint Conference on Artificial Intelligence, Hobart, Australia

Nature shows many examples where the specialisation of elements aimed to solve different problems is successful. There are explorer ants, worker bees, etc., where a group of individuals is assigned a specific task. This paper will extrapolate this ph... Read More about Improving the Performance of Multi-objective Genetic Algorithm for Function Approximation Through Parallel Islands Specialisation.

A tabu search evolutionary algorithm for solving constraint satisfaction problems. (2006)
Presentation / Conference Contribution
Craenen, B. G. W., & Paechter, B. (2006, September). A tabu search evolutionary algorithm for solving constraint satisfaction problems. Presented at Parallel Problem Solving from Nature - PPSN IX, 9th International Conference, Reykjavik, Iceland

The paper introduces a hybrid Tabu Search-Evolutionary Algorithm for solving the constraint satisfaction problem, called STLEA. Extensive experimental fine-tuning of parameters of the algorithm was performed to optimise the performance of the algorit... Read More about A tabu search evolutionary algorithm for solving constraint satisfaction problems..

A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS (2006)
Journal Article
Baños, R., Gil, C., Paechter, B., & Ortega, J. (2007). A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS. Journal of Mathematical Modelling and Algorithms, 6(2), 213-230. https://doi.org/10.1007/s10852-006-9041-6

Real optimization problems often involve not one, but multiple objectives, usually in conflict. In single-objective optimization there exists a global optimum, while in the multi-objective case no optimal solution is clearly defined but rather a set... Read More about A Hybrid Meta-Heuristic for Multi-Objective Optimization: MOSATS.

Peer-to-peer networks for scalable grid landscapes in social agent simulations. (2005)
Presentation / Conference Contribution
Craenen, B. G. W., & Paechter, B. (2005, April). Peer-to-peer networks for scalable grid landscapes in social agent simulations. Presented at AISB’05 Convention Social Intelligence and Interaction in Animals, Robots and Agents, Hatfield, UK

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..

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), Lausanne, Swizerland

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.

Fine-tuning a Genetic Algorithm for the General Timetable Problem (2005)
Presentation / Conference Contribution
Luchian, H., Ungureanasu, C., Paechter, B., & Petriuc, M. (1995, August). Fine-tuning a Genetic Algorithm for the General Timetable Problem. Presented at 1st International Conference on the Practice and Theory of Automated Timetabling (PATAT 1995), Edinburgh

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, September). An Empirical Analysis of the Grouping Genetic Algorithm: The Timetabling Case. Presented at 2005 IEEE Congress on Evolutionary Computation, Edinburgh, Scotland

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. (2002, May). Maintaining Connectivity in a Scalable and Robust Distributed Environment. Presented at 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02), Berlin, Germany

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, September). Multi-Objective Optimisation of the Pump Scheduling Problem using SPEA2. Presented at IEEE Congress on Evolutionary Computation

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..

New crossover operators for timetabling with evolutionary algorithms. (2004)
Presentation / Conference Contribution
Lewis, R. M. R., & Paechter, B. (2004, December). New crossover operators for timetabling with evolutionary algorithms

When using an evolutionary algorithm (EA) to optimise a population of feasible course timetables, it is important that the mutation and crossover operators are designed in such a way so that they don?t produce unfeasible or illegal offspring. In this... Read More about New crossover operators for timetabling with evolutionary algorithms..

PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation (2004)
Journal Article
de Toro Negro, F., Ortega, J., Ros, E., Mota, S., Paechter, B., & Martin, J. M. (2004). PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation. Parallel Computing, 30(5-6), 721-739. https://doi.org/10.1016/j.parco.2003.12.012

This paper deals with the study of the cooperation between parallel processing and evolutionary computation to obtain efficient procedures for solving multiobjective optimisation problems. We propose a new algorithm called PSFGA (parallel single fron... Read More about PSFGA: Parallel processing and evolutionary computation for multiobjective optimisation.