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MPF-FS: A multi-population framework based on multi-objective optimization algorithms for feature selection
Feature selection algorithms based on evolutionary computation have continued to emerge, and most of them have achieved outstanding results. However,...
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SonOpt: understanding the behaviour of bi-objective population-based optimisation algorithms through sound
We present an extension of SonOpt, the first ever openly available tool for the sonification of bi-objective population-based optimisation...
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Methodology for the projection of population pyramids based on Monte Carlo simulation and genetic algorithms
The analysis of the evolution of population pyramids is crucial to study and tackle the growing issue associated to the depopulation of different...
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Multi-population-based Algorithms with Different Migration Topologies and Their Improvement by Population Re-initialization
In this paper, the possibilities of improving the performance of multi-population-based algorithms were tested. In the proposed approach, it was...
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SonOpt: Sonifying Bi-objective Population-Based Optimization Algorithms
We propose SonOpt, the first (open source) data sonification application for monitoring the progress of bi-objective population-based optimization...
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Optimization Problems and Algorithms
This chapter starts by highlighting some domains of practical problems where optimization is or can be commonly applied. Then, the focus is shifted...
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A variable population size opposition-based learning for differential evolution algorithm and its applications on feature selection
The opposition-based differential evolution (ODE) cannot adaptively adjust the number of individuals partake opposition-based learning, which makes...
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Runtime Analysis of Competitive Co-evolutionary Algorithms for Maximin Optimisation of a Bilinear Function
Co-evolutionary algorithms have a wide range of applications, such as in hardware design, evolution of strategies for board games, and patching...
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Multiobjective trajectory optimization algorithms for solving multi-UAV-assisted mobile edge computing problem
The Internet of Things (IoT) devices are not able to execute resource-intensive tasks due to their limited storage and computing power. Therefore,...
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A Dual−Population Strategy Based Multi−Objective Yin−Yang−Pair Optimization for Cloud Computing
In order to improve the performance of cloud computing, the multi−objective optimization problems in this field need to be solved efficiently. This...
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Designing equitable algorithms
Predictive algorithms are now commonly used to distribute society’s resources and sanctions. But these algorithms can entrench and exacerbate...
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K-means and meta-heuristic algorithms for intrusion detection systems
In this research paper, we propose a two-stage hybrid approach that uses machine learning techniques and meta-heuristic algorithms. The first step,...
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Runtime Analyses of the Population-Based Univariate Estimation of Distribution Algorithms on LeadingOnes
We perform rigorous runtime analyses for the univariate marginal distribution algorithm ( UMDA ) and the population-based incremental learning ( PBIL )...
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DOA Estimation in the Presence of Doppler Shifts Using Quantum-Inspired Swarm Intelligence Algorithms
Direction of arrival (DOA) estimation is an important problem of wireless sensor network (WSN) where the objective is to calculate the angle of...
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A Multi-population-Based Algorithm with Different Ways of Subpopulations Cooperation
Metaheuristic methods are designed to solve continuous and discrete problems. Such methods include population based algorithms (PBAs). They are...
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A decentralized method for initial populations of genetic algorithms
Today, evolutionary algorithms are widely used in a variety of fields for problem solving and optimization purposes. The genetic algorithms (GA)...
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Creating FCM Models from Quantitative Data with Evolutionary Algorithms
The weights of an FCM can be adjusted or entirely learned from data, which addresses limitations when experts are either unsure or unavailable. In...
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Machine Learning Applications of Evolutionary and Metaheuristic Algorithms
Evolutionary algorithms and other meta-heuristic approaches enjoy widespread popularity when dealing with challenging engineering design problems...
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Graph-based algorithms for phase-type distributions
Phase-type distributions model the time until absorption in continuous or discrete-time Markov chains on a finite state space. The multivariate...
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Population-Based Structural Health Monitoring
One of the dominant challenges in data-based structural health monitoring (SHM) is the scarcity of measured data corresponding to different damage...