Optimizing Automated Manufacturing Processes Using a Hybrid BRKGA Algorithm: A Case Study on Flexible Job-Shop Scheduling-Reference-Cited by-同舟云学术

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Optimizing Automated Manufacturing Processes Using a Hybrid BRKGA Algorithm: A Case Study on Flexible Job-Shop Scheduling

Published:2024 Issue: Volume:242 Page:714-721
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Lopez-Juarez Ismael,Vazquez-Lopez Jose A,Osorio-Comparan Roman,Puente-Lira Edson E.,Hernandez-Lopez Aidee,Lefranc Gaston

Publisher

Elsevier BV

Reference12 articles.

1. Simultaneous scheduling of machines and transport robots in fexible job shop environment using hybrid metaheuristics based on clustered holonic multiagent model;Nouri;Computers & Industrial Engineering,2016

2. A hybrid genetic and variable neighborhood descent algorithm for fexible job shop scheduling problems;Gao;Computers & Operations Research,2008

3. An effective hybrid optimization approach for multi-objective fexible job-shop scheduling problems;Xia;Computers & Industrial Engineering,2005

4. Job shop scheduling optimization in real-time production control;Filip;Computers in Industry,1983

5. Simulation-based Optimization using Genetic Algorithms for Multi-objective Flexible JSSP;NICOARA;Studies in Informatics and Control,2011

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