Outputs (26)

Comparison between Single and Multi-Objective Evolutionary Algorithms to Solve the Knapsack Problem and the Travelling Salesman Problem (2020)
Journal Article
Mahrach, M., Miranda, G., León, C., & Segredo, E. (2020). Comparison between Single and Multi-Objective Evolutionary Algorithms to Solve the Knapsack Problem and the Travelling Salesman Problem. Mathematics, 8(11), Article 2018. https://doi.org/10.3390/m

One of the main components of most modern Multi-Objective Evolutionary Algorithms (MOEAs) is to maintain a proper diversity within a population in order to avoid the premature convergence problem. Due to this implicit feature that most MOEAs share, t... Read More about Comparison between Single and Multi-Objective Evolutionary Algorithms to Solve the Knapsack Problem and the Travelling Salesman Problem.

SCHOOLTHY: Automatic Menu Planner for Healthy and Balanced School Meals (2020)
Journal Article
Segredo, E., Miranda, G., Ramos, J. M., Leon, C., & Rodriguez-Leon, C. (2020). SCHOOLTHY: Automatic Menu Planner for Healthy and Balanced School Meals. IEEE Access, 8, 113200-113218. https://doi.org/10.1109/access.2020.3003067

SCHOOLTHY: Automatic Menu Planner for Healthy and Balanced School Meals is a decision support tool that addresses the multi-objective menu planning problem in order to automatically produce meal plans for school canteens. Malnutrition is a widespread... Read More about SCHOOLTHY: Automatic Menu Planner for Healthy and Balanced School Meals.

Simulador de Robótica Educativa para la promoción del Pensamiento Computacional | Educational Robotics simulator for fostering Computational Thinking (2020)
Journal Article
Ángel-Díaz, C. M., Segredo, E., Arnay, R., & León, C. (2020). Simulador de Robótica Educativa para la promoción del Pensamiento Computacional | Educational Robotics simulator for fostering Computational Thinking. RED. Revista de Educación a Distanci

Este trabajo presenta una herramienta Web libre y gratuita que facilita a cualquier centro educativo la enseñanza de conceptos básicos sobre robótica y programación y que, al mismo tiempo, permite desarrollar habilidades relacionadas con el pensamien... Read More about Simulador de Robótica Educativa para la promoción del Pensamiento Computacional | Educational Robotics simulator for fostering Computational Thinking.

A similarity-based neighbourhood search for enhancing the balance exploration–exploitation of differential evolution (2019)
Journal Article
Segredo, E., Lalla-Ruiz, E., Hart, E., & Voß, S. (2020). A similarity-based neighbourhood search for enhancing the balance exploration–exploitation of differential evolution. Computers and Operations Research, 117, Article 104871. https://doi.org/10.10

The success of search-based optimisation algorithms depends on appropriately balancing exploration and exploitation mechanisms during the course of the search. We introduce a mechanism that can be used with Differential Evolution (de) algorithms to a... Read More about A similarity-based neighbourhood search for enhancing the balance exploration–exploitation of differential evolution.

Optimising Real-World Traffic Cycle Programs by Using Evolutionary Computation (2019)
Journal Article
Segredo, E., Luque, G., Segura, C., & Alba, E. (2019). Optimising Real-World Traffic Cycle Programs by Using Evolutionary Computation. IEEE Access, 7, 43915-43932. https://doi.org/10.1109/ACCESS.2019.2908562

Traffic congestion, and the consequent loss of time, money, quality of life, and higher pollution, is currently one of the most important problems in cities, and several approaches have been proposed to reduce it. In this paper, we propose a novel for... Read More about Optimising Real-World Traffic Cycle Programs by Using Evolutionary Computation.

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.

Selection methods and diversity preservation in many-objective evolutionary algorithms (2018)
Journal Article
Martí, L., Segredo, E., Sánchez-Pi, N., & Hart, E. (2018). Selection methods and diversity preservation in many-objective evolutionary algorithms. Data Technologies and Applications, https://doi.org/10.1108/dta-01-2018-0009

Purpose – One of the main components of multi-objective, and therefore, many-objective evolutionary algorithms is the selection mechanism. It is responsible for performing two main tasks simultaneously. First, it has to promote convergence by selecti... Read More about Selection methods and diversity preservation in many-objective evolutionary algorithms.

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.

On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems (2018)
Journal Article
Voß, S., Segredo, E., Lalla-Ruiz, E., Hart, E., & Voss, S. (2018). On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems. Expert Systems with Applications, 102

Migrating Birds Optimisation (mbo) is a nature-inspired approach which has been shown to be very effective when solving a variety of combinatorial optimisation problems. More recently, an adaptation of the algorithm has been proposed that enables it... Read More about On the performance of the hybridisation between migrating birds optimisation variants and differential evolution for large scale continuous problems.

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). Impact of selection methods on the diversity of many-objective Pareto set approximations. Procedia Computer Science, 112, 844-853. https://doi.org/10.1016/j.procs.2017.08.077

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.