Cellular particle swarm optimization with a simple adaptive local search strategy for the permutation flow shop scheduling problem-Reference-Cited by-同舟云学术

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Cellular particle swarm optimization with a simple adaptive local search strategy for the permutation flow shop scheduling problem

Published:2023-07-26 Issue: Volume: Page:
ISSN:1230-2384
Container-title:Archives of Control Sciences
language:pl
Short-container-title:

Author:

Seck-Tuoh-Mora Juan C.,Medina-Marin Joselito,Martinez-Gomez Erick S.,Hernandez-Gress Eva S.,Hernandez-Romero Norberto,Volpi-Leon Valeria

Publisher

Polish Academy of Sciences Chancellery

Subject

Control and Optimization,Modeling and Simulation,Control and Systems Engineering

Link

https://journals.pan.pl/Content/112918/PDF/acsc-29-2-1.pdf

Cited by 5 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. Method of rescheduling for hybrid production lines with intermediate buffers;Archives of Control Sciences;2023-07-26

2. A sinusoidal social learning swarm optimizer for large-scale optimization;Knowledge-Based Systems;2023-01

3. A Hybrid Search Using Genetic Algorithms and Random-Restart Hill-Climbing for Flexible Job Shop Scheduling Instances with High Flexibility;Applied Sciences;2022-08-11

4. A New Algorithm Inspired on Reversible Elementary Cellular Automata for Global Optimization;IEEE Access;2022

5. Academic Insights and Perspectives: Cellular Automata and Production Scheduling;Mathematical Problems in Engineering;2020-08-06

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