• A General Framework Based on Walsh Decomposition for Combinatorial Optimization Problems 

  Unanue, I.; Merino, M.; Lozano, J.A. (2021-01-01)

  In this paper we pursue the use of the Fourier transform for a general analysis of combinatorial optimization problems. While combinatorial optimization problems are defined by means of different notions like weights in a ...

• A mathematical analysis of EDAs with distance-based exponential models 

  Unanue, I.; Merino, M.; Lozano, J.A. (2022-09-01)

  Estimation of Distribution Algorithms have been successfully used to solve permutation-based Combinatorial Optimization Problems. In this case, the algorithms use probabilistic models specifically designed for codifying ...

• PyDDRBG: A Python framework for benchmarking and evaluating static and dynamic multimodal optimization methods 

  Ahrari, A.; Elsayed, S.; Sarker, R.; Essam, D.; Coello, C.A. (2022-01-01)

  PyDDRBG is a Python framework for generating tunable test problems for static and dynamic multimodal optimization. It allows for quick and simple generation of a set of predefined problems for non-experienced users, as ...

• Preference incorporation into many-objective optimization: An Ant colony algorithm based on interval outranking 

  Rivera, G.; Coello, C.A.; Cruz-Reyes, L.; Fernandez, E.R.; Gomez-Santillan, C.; Rangel-Valdez, N. (2022-03-01)

  In this paper, we enriched Ant Colony Optimization (ACO) with interval outranking to develop a novel multi-objective ACO optimizer to approach problems with many objective functions. This proposal is suitable if the ...

• COARSE-EMOA: An indicator-based evolutionary algorithm for solving equality constrained multi-objective optimization problems 

  Llano García, J.L.; Monroy, R.; Sosa Hernández, V.A.; Coello, C.A. (2021-12-01)

  Many real-world applications involve dealing with several conflicting objectives which need to be optimized simultaneously. Moreover, these problems may require the consideration of limitations that restrict their decision ...

• Parallel Multi-Objective Evolutionary Algorithms: A Comprehensive Survey 

  Falcón-Cardona, J.G.; Hernández Gómez, R.; Coello, C.A.; Castillo Tapia, M.G. (2021-12-01)

  Multi-Objective Evolutionary Algorithms (MOEAs) are powerful search techniques that have been extensively used to solve difficult problems in a wide variety of disciplines. However, they can be very demanding in terms of ...

• A Novel Parametric benchmark generator for dynamic multimodal optimization 

  Ahrari, A.; Elsayed, S.; Sarker, R.; Essam, D.; Coello, C.A. (2021-08-01)

  In most existing studies on dynamic multimodal optimization (DMMO), numerical simulations have been performed using the Moving Peaks Benchmark (MPB), which is a two-decade-old test suite that cannot simulate some critical ...

• On the Effect of the Cooperation of Indicator-Based Multiobjective Evolutionary Algorithms 

  Falcon-Cardona, J.G; Ishibuchi, H.; Coello, C.A.; Emmerich, M. (2021-08-01)

  For almost 20 years, quality indicators (QIs) have promoted the design of new selection mechanisms of multiobjective evolutionary algorithms (MOEAs). Each indicator-based MOEA (IB-MOEA) has specific search preferences ...

• CURIE: a cellular automaton for concept drift detection 

  Lobo, J.L.; Del Ser, J.; Osaba, E.; Bifet, A.; Herrera, F. (2021-11-01)

  Data stream mining extracts information from large quantities of data flowing fast and continuously (data streams). They are usually affected by changes in the data distribution, giving rise to a phenomenon referred to as ...

• LUNAR: Cellular automata for drifting data streams 

  Lobo, J.L.; Del Ser, J.; Herrera, F. (2021-01-08)

  With the advent of fast data streams, real-time machine learning has become a challenging task, demanding many processing resources. In addition, they can be affected by the concept drift effect, by which learning methods ...

• AT-MFCGA: An Adaptive Transfer-guided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking 

  Osaba, E.; Del Ser, J.; Martínez, A.D.; Lobo, J.L.; Herrera, F. (2021-09-01)

  Transfer Optimization is an incipient research area dedicated to solving multiple optimization tasks simultaneously. Among the different approaches that can address this problem effectively, Evolutionary Multitasking resorts ...

• Wireless Network Optimization for Massive V2I Data Collection using Multiobjective Harmony Search Heuristics 

  Sobron, I.; Alonso, B.; Del Ser, J.; Vélez, M. (2017)

  This paper proposes to improve the efficiency of the deploy- ment of wireless network infrastructure for massive data collection from vehicles over regional areas. The increase in the devices that are carried by vehicles ...

• Cost-efficient Selective Network Caching in Large-Area Vehicular Networks using Multi-objective Heuristics 

  Perfecto, C.; Bilbao, M.N.; Del Ser, J. (2017)

  In the last decade the interest around network caching tech- niques has augmented notably for alleviating the ever-growing demand of resources by end users in mobile networks. This gained momentum stems from the fact that ...

• On the Creation of Diverse Ensembles for Nonstationary Environments using Bio-inspired Heuristics 

  Lobo, J.L.; Del Ser, J.; Villar-Rodriguez, E.; Salcedo-Sanz, S.; Bilbao, M.N. (2017)

  Recently the relevance of adaptive models for dynamic data environments has turned into a hot topic due to the vast number of sce- narios generating nonstationary data streams. When a change (concept drift) in data ...

• An Analysis of Coalition-Competition Pricing Strategies for Multi-Operator Mobile Traffic Offloading using Bi-objective Heuristics 

  Consul, J.; Perfecto, C.; Del Ser, J.; Bilbao, M.N. (2017)

  In a competitive market relationships between telecommuni- cations operators serving simultaneously over a certain geographical area are diverse and motivated by very different business strategies and goals. Such relationships ...

• A Heuristically Optimized Complex Event Processing Engine for Big Data Stream Analytics 

  Olabarrieta, I.; Del Ser, J.; Torre-Bastida, A.I.; Campos-Cordobes, S.; Laña, I. (2017)

  This paper describes a Big Data stream analytics platform developed within the DEWI project for processing upcoming events from wireless sensors installed in a truck. The platform consists of a Complex Event Processing ...

• Quantitative Analysis and Performance Study of Ant Colony Optimization Models Applied to Multi-Mode Resource Constraint Project Scheduling Problem 

  Gonzalez-Pardo, A.; Del Ser, J.; Camacho, D. (2017)

  Constraint Satisfaction Problems (CSP) belongs to this kind of traditional NP-hard problems with a high impact in both, research and industrial domains. However, due to the complexity that CSP problems exhibit, researchers ...

• A Novel Grouping Harmony Search Algorithm for Clustering Problems 

  Landa-Torres, I.; Del Ser, J.; Manjarres, D.; Gil-Lopez, S.; Salcedo-Sanz, S. (2017)

  The problem of partitioning a data set into disjoint groups or clusters of related items plays a key role in data analytics, in particular when the information retrieval becomes crucial for further data analysis. In this ...

• Joint Feature Selection and Parameter Tuning for Short-term Traffic Flow Forecasting based on Heuristically Optimized Multi-layer Neural Networks 

  Oregi, I.; Del Ser, J.; Laña, I.; Vélez, M. (2017)

  Short-term traffic flow forecasting is a vibrant research topic that has been growing in interest since the late 70’s. In the last decade this vibrant field has shifted its focus towards machine learning methods. These ...

• A Feature Selection Method for Author Identification in Interactive Communications based on Supervised Learning and Language Typicality 

  Villar-Rodriguez, E.; Del Ser, J.; Bilbao, M.N.; Salcedo-Sanz, S. (2016)

  Authorship attribution, conceived as the identification of the origin of a text be- tween different authors, has been a very active area of research in the scientific community mainly supported by advances in Natural ...

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