Memetic Computing

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A decomposition-based evolutionary algorithm for scalable multi/many-objective optimization
Memetic Computing - Tập 13 - Trang 413-432 - 2021
Jiaxin Chen, Jinliang Ding, Kay Chen Tan, Qingda Chen
The aim of evolutionary multi/many-objective optimization is to obtain a set of Pareto-optimal solutions with good trade-off among the multiple conflicting objectives. However, the convergence and diversity of multiobjective evolutionary algorithms often seriously decrease with the number of objectives and decision variables increasing. In this paper, we present a decomposition-based evolutionary ...... hiện toàn bộ
Extreme learning machine via free sparse transfer representation optimization
Memetic Computing - Tập 8 - Trang 85-95 - 2016
Xiaodong Li, Weijie Mao, Wei Jiang, Ye Yao
In this paper, we propose a general framework for Extreme Learning Machine via free sparse transfer representation, which is referred to as transfer free sparse representation based on extreme learning machine (TFSR-ELM). This framework is suitable for different assumptions related to the divergence measures of the data distributions, such as a maximum mean discrepancy and K-L divergence. We propo...... hiện toàn bộ
Thermal image colorization using Markov decision processes
Memetic Computing - - 2017
Xiaojing Gu, Mengchi He, Xingsheng Gu
Integrating memetic search into the BioHEL evolutionary learning system for large-scale datasets
Memetic Computing - Tập 5 - Trang 95-130 - 2013
Dan Andrei Calian, Jaume Bacardit
Local search methods are widely used to improve the performance of evolutionary computation algorithms in all kinds of domains. Employing advanced and efficient exploration mechanisms becomes crucial in complex and very large (in terms of search space) problems, such as when employing evolutionary algorithms to large-scale data mining tasks. Recently, the GAssist Pittsburgh evolutionary learning s...... hiện toàn bộ
A novel location-based DNA matching algorithm for hyperspectral image classification
Memetic Computing - Tập 11 - Trang 175-191 - 2018
Ronghua Shang, Yuyang Lan, Licheng Jiao
Recently, hyperspectral image classification is attracting more and more attention. Since every pixel is represented by a high dimensional spectral vector, the ordinary machine learning algorithms usually require a large number of training samples to solve this problem. However, collecting labeled samples is time-consuming, which forces us to improve existing algorithms. Motivated by evolutional a...... hiện toàn bộ
A benchmark for cooperative coevolution
Memetic Computing - Tập 4 - Trang 263-277 - 2012
Alberto Tonda, Evelyne Lutton, Giovanni Squillero
Cooperative co-evolution algorithms (CCEA) are a thriving sub-field of evolutionary computation. This class of algorithms makes it possible to exploit more efficiently the artificial Darwinist scheme, as soon as an optimisation problem can be turned into a co-evolution of interdependent sub-parts of the searched solution. Testing the efficiency of new CCEA concepts, however, it is not straightforw...... hiện toàn bộ
Deep memetic models for combinatorial optimization problems: application to the tool switching problem
Memetic Computing - - 2019
Jhon Edgar Amaya, Carlos Cotta, Antonio J. Fernández-Leiva, Pablo García-Sánchez
Memetic algorithms are techniques that orchestrate the interplay between population-based and trajectory-based algorithmic components. In particular, some memetic models can be regarded under this broad interpretation as a group of autonomous basic optimization algorithms that interact among them in a cooperative way in order to deal with a specific optimization problem, aiming to obtain better re...... hiện toàn bộ
An effective memetic algorithm for UAV routing and orientation under uncertain navigation environments
Memetic Computing - Tập 13 - Trang 169-183 - 2021
Shang Xiang, Ling Wang, Lining Xing, Yonghao Du
Navigation correction is usually frequently required by unmanned aerial vehicles (UAVs), especially under uncertain navigation environments. Although the UAV’s straight flights that connect navigation correction points can constitute a plan of navigation corrections, the underlying attitude orientations of the UAV when flying through the visited points are also required by appropriate steering mot...... hiện toàn bộ
A simple and scalable particle swarm optimization structure based on linear system theory
Memetic Computing - - 2024
Jian Zhu, Jianhua Liu
Since it was first presented, particle swarm optimization (PSO) has experienced numerous improvements as a traditional optimization approach. PSO becomes more complex as a result of the majority of improvement strategies, which use learning model replacement or parameter adjustment to enhance PSO’s performance. Based on linear system theory, this study proposes a simple and scalable framework for ...... hiện toàn bộ
A constrained multi-objective optimization algorithm with two cooperative populations
Memetic Computing - Tập 14 - Trang 95-113 - 2022
Jianlin Zhang, Jie Cao, Fuqing Zhao, Zuohan Chen
Constrained multi-objective problems (CMOPs) require balancing convergence, diversity, and feasibility of solutions. Unfortunately, the existing constrained multi-objective optimization algorithms (CMOEAs) exhibit poor performance when solving the CMOPs with complex feasible regions. To solve this shortcoming, this work proposes an improved algorithm named the CMOEA-TCP, which maintains two popula...... hiện toàn bộ
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