All Outputs (9)

A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem (2022)
Presentation / Conference Contribution
Marrero, A., Segredo, E., León, C., & Hart, E. (2022, September). A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem. Presented at Parallel Problem Solving from Nature – PPSN XVII, 17th International Conference, Dortmund, Germany

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 instances that are diverse with respect to a feature-space but also elicit... Read More about A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem.

How do young students get enthusiastic about computational thinking activities? (2021)
Presentation / Conference Contribution
Herrero Álvarez, R., León, C., Miranda, G., Segredo, E., Socas, Ó., Cuellar-Moreno, M., Caballero-Julia, D., García, L., & Díaz, Y. (2021, July). How do young students get enthusiastic about computational thinking activities?. Presented at 13th International Conference on Education and New Learning Technologies, Online

This paper presents a study of the emotions that are produced in pre-university students when performing Computational Thinking activities. In the absence of an official document that deals what content of Computational Thinking should be taught at t... Read More about How do young students get enthusiastic about computational thinking activities?.

A Cooperative Learning Approach for the Quadratic Knapsack Problem (2018)
Presentation / Conference Contribution
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 several applications in different fields such as telecommunications, graph theor... Read More about A Cooperative Learning Approach for the Quadratic Knapsack Problem.

A novel similarity-based mutant vector generation strategy for differential evolution (2018)
Presentation / Conference Contribution
Segredo, E., Lalla-Ruiz, E., & Hart, E. (2018, July). A novel similarity-based mutant vector generation strategy for differential evolution. Presented at The Genetic and Evolutionary Computation Conference 2018 (GECCO 2018), Kyoto, Japan

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 search space. However, it is also responsible for promoting intensificatio... Read More about A novel similarity-based mutant vector generation strategy for differential evolution.

Impact of selection methods on the diversity of many-objective Pareto set approximations (2017)
Presentation / Conference Contribution
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2017, September). Impact of selection methods on the diversity of many-objective Pareto set approximations. Presented at 21st International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Marseille, France

Selection methods are a key component of all multi-objective and, consequently, many-objective optimisation evolutionary algorithms. They must perform two main tasks simultaneously. First of all, they must select individuals that are as close as poss... Read More about Impact of selection methods on the diversity of many-objective Pareto set approximations.

The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles (2017)
Presentation / Conference Contribution
Segura, C., Segredo, E., & Miranda, G. (2017, June). The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles. Presented at 2017 IEEE Congress on Evolutionary Computation (CEC)

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 extends state-of-the-art schemes for dealing with Sudoku puzzles of larger dim... Read More about The importance of the individual encoding in memetic algorithms with diversity control applied to large Sudoku puzzles.

Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation (2016)
Presentation / Conference Contribution
Segredo, E., Lalla-Ruiz, E., Hart, E., Paechter, B., & Voß, S. (2016, May). Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation. Presented at Learning and Intelligent OptimizatioN Conference LION 10, Ischia Island (Napoli), Italy

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 which can apply one of two meta-heuristics at the current stage of the search.... Read More about Hybridisation of Evolutionary Algorithms through hyper-heuristics for global continuous optimisation.

Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems (2016)
Presentation / Conference Contribution
Segredo, E., Paechter, B., Hart, E., & Gonz´alez-Vila, C. I. (2016, July). Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems. Presented at IEEE World Congress on Computational Intelligence

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 scheme based on both Fuzzy Logic Controllers (FLCs) and Hyper-heuristics (HHs).... Read More about Hybrid parameter control approach applied to a diversity-based multi-objective Memetic Algorithm for frequency assignment problems.

Analysing the performance of migrating birds optimisation approaches for large scale continuous problems (2016)
Presentation / Conference Contribution
Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E., & Paechter, B. (2016, September). Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. Presented at 14th International Conference on Parallel Problem Solving from Nature (PPSN 2016)

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 Optimisation (mbo) and Multi-leader Migrating Birds Optimisation (mmbo), t... Read More about Analysing the performance of migrating birds optimisation approaches for large scale continuous problems.