Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (in press)
Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. In Genetic and Evolutionary Computation Conference (GECCO ’24), July 14–18, 2024, Melbourne, VIC, Australia. https://doi.org/10.1145/3638529.3654028
The ability to generate example instances from a domain is important in order to benchmark algorithms and to generate data that covers an instance-space in order to train mach...
A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (2022)
A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem. In Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022 (223-236). https://doi.org/10.1007/978-3-031-14714-2_16
We propose a new approach to generating synthetic instances in the knapsack domain in order to fill an instance-space. The method uses a novelty-search algorithm to search for...
A Cooperative Learning Approach for the Quadratic Knapsack Problem
Conference Proceeding
Lalla-Ruiz, E., Segredo, E., & Voß, S. (2018)
A Cooperative Learning Approach for the Quadratic Knapsack Problem. In Learning and Intelligent Optimization Conference (LION12). , (31-35). https://doi.org/10.1007/978-3-030-05348-2_3
The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has sever...
A novel similarity-based mutant vector generation strategy for differential evolution
Conference Proceeding
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018)
A novel similarity-based mutant vector generation strategy for differential evolution. In H. Aguirre (Ed.), Proceedings of the Genetic and Evolutionary Computation Conference 2018https://doi.org/10.1145/3205455.3205628
The mutant vector generation strategy is an essential component of Differential Evolution (DE), introduced to promote diversity, resulting in exploration of novel areas of the...
The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles
Conference Proceeding
Segura, C., Segredo, E., & Miranda, G. (2017)
The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles. In 2017 IEEE Congress on Evolutionary Computation (CEC). https://doi.org/10.1109/CEC.2017.7969565
In recent years, several memetic algorithms with explicit mechanisms to delay convergence have shown great promise when solving 9x9 Sudoku puzzles. This paper analyzes and ext...
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...