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Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation

Conference Proceeding
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016)
Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization: 10th International Conference, LION 10, Ischia, Italy, May 29 -- June 1, 2016, (296-305). https://doi.org/10.1007/978-3-319-50349-3_25
Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorithm Selection Problem was first posed. Here we propose a hyper-heuristic whic...

Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems

Conference Proceeding
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016)
Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. In 2016 IEEE Congress on Evolutionary Computation (CEC)https://doi.org/10.1109/CEC.2016.7743969
In order to address the difficult issue of parameter setting within a diversity-based Multi-objective Evolutionary Algorithm (MOEA), we recently proposed a hybrid control sche...

Analysing the performance of migrating birds optimisation approaches for large scale continuous problems

Conference Proceeding
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016)
Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. In Parallel Problem Solving from Nature – PPSN XIV, (134-144). https://doi.org/10.1007/978-3-319-45823-6_13
We present novel algorithmic schemes for dealing with large scale continuous problems. They are based on the recently proposed population-based meta-heuristics Migrating Birds...

The Cost of Communication: Environmental Pressure and Survivability in mEDEA

Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2015)
The Cost of Communication: Environmental Pressure and Survivability in mEDEA. In Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference - GECCO Companion '15, 1239-1240. doi:10.1145/2739482.2768489
We augment the mEDEA algorithm to explicitly account for the costs of communication between robots. Experimental results show that adding a costs for communication exerts envi...

Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication.

Conference Proceeding
Hart, E., Steyven, A., & Paechter, B. (2015)
Improving survivability in environment-driven distributed evolutionary algorithms through explicit relative fitness and fitness proportionate communication. In Proceedings of the 2015 on Genetic and Evolutionary Computation Conference - GECCO '15, (169-176). https://doi.org/10.1145/2739480.2754688
Ensuring the integrity of a robot swarm in terms of maintaining a stable population of functioning robots over long periods of time is a mandatory prerequisite for building mo...

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...

On the comparison of initialisation strategies in differential evolution for large scale optimisation

Journal Article
Segredo, E., Paechter, B., Segura, C., & González-Vila, C. I. (2018)
On the comparison of initialisation strategies in differential evolution for large scale optimisation. Optimization Letters, 12(1), 221-234. https://doi.org/10.1007/s11590-017-1107-z
Differential Evolution (DE) has shown to be a promising global opimisation solver for continuous problems, even for those with a large dimensionality. Different previous works...

An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics

Conference Proceeding
Steyven, A., Hart, E., & Paechter, B. (2017)
An investigation of environmental influence on the benefits of adaptation mechanisms in evolutionary swarm robotics. In GECCO '17 Proceedings of the Genetic and Evolutionary, (155-162). https://doi.org/10.1145/3071178.3071232
A robotic swarm that is required to operate for long periods in a potentially unknown environment can use both evolution and individual learning methods in order to adapt. How...

2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms

Conference Proceeding
Lapok, P., Lawson, A., & Paechter, B. (2018)
2-Dimensional Outline Shape Representation for Generative Design with Evolutionary Algorithms. In H. Rodrigues, J. Herskovits, C. Mota Soares, A. Araújo, J. Guedes, J. Folgado, …J. Madeira (Eds.), EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization, 926-937. doi:10.1007/978-3-319-97773-7_80
In this paper, we investigate the ability of genetic representation methods to describe two-dimensional outline shapes, in order to use them in a generative design system. A s...

A local search for the timetabling problem.

Conference Proceeding
Rossi-Doria, O., Blum, C., Knowles, J., Sampels, M., Socha, K., & Paechter, B. (2001)
A local search for the timetabling problem. In E. Burke, & P. Causmaecker (Eds.), Proceedings of the Conference on the Practice and Theory of Automated Timetabling (PATAT 2002), 124-127
This work is part of the Metaheuristic Network, a European Commission project that seeks to empirically compare the performance of various metaheuristics on different combinat...