A multitasking multi-objective differential evolution gene selection algorithm enhanced with new elite and guidance strategies for tumor identification
M Li, Y Zhao, M Lou, S Deng, L Wang - Expert Systems with Applications, 2024 - Elsevier
A key preprocessing step in tumor recognition based on microarray expression profile data
and machine learning is to identify tumor marker genes. Gene selection aims to select the …
and machine learning is to identify tumor marker genes. Gene selection aims to select the …
Symmetric uncertainty based decomposition multi-objective immune algorithm for feature selection
Z Chai, W Li, Y Li - Swarm and Evolutionary Computation, 2023 - Elsevier
Feature selection (FS) is a significant data preprocessing technology in many fields. FS
generally has two primary conflicting goals: 1) reducing features number and 2) improving …
generally has two primary conflicting goals: 1) reducing features number and 2) improving …
Decomposition multi-objective evolutionary optimization: From state-of-the-art to future opportunities
K Li - arXiv preprint arXiv:2108.09588, 2021 - arxiv.org
Decomposition has been the mainstream approach in the classic mathematical
programming for multi-objective optimization and multi-criterion decision-making. However …
programming for multi-objective optimization and multi-criterion decision-making. However …
A decomposition-based multi-objective immune algorithm for feature selection in learning to rank
W Li, Z Chai, Z Tang - Knowledge-Based Systems, 2021 - Elsevier
Abstract Learning-to-rank (L2R) based on feature selection has been proved effectively.
However, feature selection problem is more challenging due to two conflicting objectives …
However, feature selection problem is more challenging due to two conflicting objectives …
Parallel fractional dominance MOEAs for feature subset selection in big data
In this paper, we solve the feature subset selection (FSS) problem with three objective
functions namely, cardinality, area under receiver operating characteristic curve (AUC) and …
functions namely, cardinality, area under receiver operating characteristic curve (AUC) and …
Research on decomposition-based multi-objective evolutionary algorithm with dynamic weight vector
J Zhao, X Huang, T Li, H Yu, H Fei, Q Yang - Journal of Computational …, 2024 - Elsevier
In recent years, multi-objective evolutionary algorithm based on decomposition has
gradually attracted people's interest. However, this algorithm has some problems. For …
gradually attracted people's interest. However, this algorithm has some problems. For …
A Survey of Multi-objective Evolutionary Algorithm Based on Decomposition: Past and Future
K Li - IEEE Transactions on Evolutionary Computation, 2024 - ieeexplore.ieee.org
Decomposition has been the mainstream approach in the classic mathematical
programming for multi-objective optimization and multi-criterion decision-making. However …
programming for multi-objective optimization and multi-criterion decision-making. However …
Cooperative, collaborative, coevolutionary multi-objective optimization on CPU-GPU multi-core
Z Sun, YY Liu, P Thulasiraman - The Journal of Supercomputing, 2025 - Springer
Coevolutionary multi-objective heuristics solve multi-objective optimization problems by
evolving two different heuristics, simultaneously while exchanging information to produce …
evolving two different heuristics, simultaneously while exchanging information to produce …
A Survey of Decomposition-Based Evolutionary Multi-Objective Optimization: Part I-Past and Future
K Li - arXiv preprint arXiv:2404.14571, 2024 - arxiv.org
Decomposition has been the mainstream approach in classic mathematical programming for
multi-objective optimization and multi-criterion decision-making. However, it was not …
multi-objective optimization and multi-criterion decision-making. However, it was not …
并行智能优化算法研究进展.
张国， 王锐， 雷洪涛， 张涛… - Control Theory & …, 2023 - search.ebscohost.com
基于种群迭代搜索的智能优化算法在农业, 交通, 工业等很多领域都取得了广泛的应用.
但是该类算法迭代寻优的特点使其求解效率通常较低, 很难应用到大规模 …
但是该类算法迭代寻优的特点使其求解效率通常较低, 很难应用到大规模 …