activity
20162021
most citeddMFEA-II: An Adaptive Multifactorial Evolutionary Algorithm for Permutation-based Discrete Optimization Problems

23 citations · 26 across the 6 of their papers we have counts for

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8 papers · 1 filter

cs.NE2021

Evolutionary Multitask Optimization: a Methodological Overview, Challenges and Future Research Directions

Eneko Osaba, Aritz D. Martinez, Javier Del Ser

In this work we consider multitasking in the context of solving multiple optimization problems simultaneously by conducting a single search process. The principal goal when dealing…

cs.NE20203 cited

A Coevolutionary Variable Neighborhood Search Algorithm for Discrete Multitasking (CoVNS): Application to Community Detection over Graphs

Eneko Osaba, Esther Villar-Rodriguez, Javier Del Ser

The main goal of the multitasking optimization paradigm is to solve multiple and concurrent optimization tasks in a simultaneous way through a single search process. For attaining…

cs.NE2020

Lights and Shadows in Evolutionary Deep Learning: Taxonomy, Critical Methodological Analysis, Cases of Study, Learned Lessons, Recommendations and Challenges

Aritz D. Martinez, Javier Del Ser, Esther Villar-Rodriguez +5

Much has been said about the fusion of bio-inspired optimization algorithms and Deep Learning models for several purposes: from the discovery of network topologies and hyper-parame…

cs.NE2020

Deep Echo State Networks for Short-Term Traffic Forecasting: Performance Comparison and Statistical Assessment

Javier Del Ser, Ibai Lana, Eric L. Manibardo +5

In short-term traffic forecasting, the goal is to accurately predict future values of a traffic parameter of interest occurring shortly after the prediction is queried. The activit…

cs.NE2020

COEBA: A Coevolutionary Bat Algorithm for Discrete Evolutionary Multitasking

Eneko Osaba, Javier Del Ser, Xin-She Yang +2

Multitasking optimization is an emerging research field which has attracted lot of attention in the scientific community. The main purpose of this paradigm is how to solve multiple…

cs.NE2020

Multifactorial Cellular Genetic Algorithm (MFCGA): Algorithmic Design, Performance Comparison and Genetic Transferability Analysis

Eneko Osaba, Aritz D. Martinez, Jesus L. Lobo +2

Multitasking optimization is an incipient research area which is lately gaining a notable research momentum. Unlike traditional optimization paradigm that focuses on solving a sing…