Heuristic Optimization
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A General Framework Based on Walsh Decomposition for Combinatorial Optimization Problems
(20210101)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 distancebased exponential models
(20220901)Estimation of Distribution Algorithms have been successfully used to solve permutationbased 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
(20220101)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 nonexperienced users, as ... 
Preference incorporation into manyobjective optimization: An Ant colony algorithm based on interval outranking
(20220301)In this paper, we enriched Ant Colony Optimization (ACO) with interval outranking to develop a novel multiobjective ACO optimizer to approach problems with many objective functions. This proposal is suitable if the ... 
COARSEEMOA: An indicatorbased evolutionary algorithm for solving equality constrained multiobjective optimization problems
(20211201)Many realworld 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 MultiObjective Evolutionary Algorithms: A Comprehensive Survey
(20211201)MultiObjective 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
(20210801)In most existing studies on dynamic multimodal optimization (DMMO), numerical simulations have been performed using the Moving Peaks Benchmark (MPB), which is a twodecadeold test suite that cannot simulate some critical ... 
On the Effect of the Cooperation of IndicatorBased Multiobjective Evolutionary Algorithms
(20210801)For almost 20 years, quality indicators (QIs) have promoted the design of new selection mechanisms of multiobjective evolutionary algorithms (MOEAs). Each indicatorbased MOEA (IBMOEA) has specific search preferences ... 
CURIE: a cellular automaton for concept drift detection
(20211101)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
(20210108)With the advent of fast data streams, realtime 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 ... 
ATMFCGA: An Adaptive Transferguided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking
(20210901)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
(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 ... 
Costefficient Selective Network Caching in LargeArea Vehicular Networks using Multiobjective Heuristics
(2017)In the last decade the interest around network caching tech niques has augmented notably for alleviating the evergrowing 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 Bioinspired Heuristics
(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 CoalitionCompetition Pricing Strategies for MultiOperator Mobile Traffic Offloading using Biobjective Heuristics
(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
(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 MultiMode Resource Constraint Project Scheduling Problem
(2017)Constraint Satisfaction Problems (CSP) belongs to this kind of traditional NPhard 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
(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 Shortterm Traffic Flow Forecasting based on Heuristically Optimized Multilayer Neural Networks
(2017)Shortterm 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
(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 ...