Multi-objective particle swarm optimization for key quality feature selection in complex manufacturing processes-Reference-Cited by-同舟云学术

Multi-objective particle swarm optimization for key quality feature selection in complex manufacturing processes

Published:2023-09 Issue: Volume:641 Page:119062
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Li An-Da^ORCID,Xue Bing,Zhang Mengjie

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference50 articles.

1. On the approximability of minimizing nonzero variables or unsatisfied relations in linear systems;Amaldi;Theor. Comput. Sci.,1998

2. Multicriteria variable selection for classification of production batches;Anzanello;Eur. J. Oper. Res.,2012

3. Developing new fitness functions in genetic programming for classification with unbalanced data;Bhowan;IEEE Trans. Syst. Man Cybern., Part B, Cybern.,2012

4. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: Solving problems with box constraints;Deb;IEEE Trans. Evol. Comput.,2014

5. A fast and elitist multiobjective genetic algorithm: NSGA-II;Deb;IEEE Trans. Evol. Comput.,2002

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-guided population co-evolutionary algorithm based on multiple similarity decomposition for large-scale flexible job shop scheduling problem;Applied Soft Computing;2024-11

2. Theoretical insights into recombination mechanisms and design optimization of BaZrS3 chalcogenide perovskite solar cells;Applied Physics A;2024-09-14

3. Information gain-based multi-objective evolutionary algorithm for feature selection;Information Sciences;2024-08

4. A multi-strategy driven reinforced hierarchical operator in the grey wolf optimizer for feature selection;Information Sciences;2024-08

5. MPEA-FS: A decomposition-based multi-population evolutionary algorithm for high-dimensional feature selection;Expert Systems with Applications;2024-08