Robotic flow shop scheduling with parallel machines and no-wait constraints in an aluminium anodising plant with the CMAES algorithm

Carina M. Behr, Jacomine Grobler*

*Corresponding author for this work

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This paper proposes a covariance matrix adaptation evolution strategy (CMAES) based algorithm for a robotic flow shop scheduling problem with multiple robots and parallel machines. The algorithm is compared to three popular scheduling rules as well as existing schedules at a South African anodising plant. The CMAES algorithm statistically significantly outperformed all other algorithms for the size of problems currently scheduled by the anodising plant. A sensitivity analysis was also conducted on the number of tanks required at critical stages in the process to determine the effectiveness of the CMAES algorithm in assisting the anodising plant to make business decisions.

Original languageEnglish
Title of host publicationArtificial Intelligence and Soft Computing - 17th International Conference, ICAISC 2018, Proceedings
EditorsLeszek Rutkowski, Rafal Scherer, Marcin Korytowski, Witold Pedrycz, Ryszard Tadeusiewicz, Jacek M. Zurada
Number of pages11
ISBN (Electronic)978-3-319-91253-0
ISBN (Print)978-3-319-91252-3
Publication statusPublished - 1 Jan 2018
Event17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018 - Mercure Zakopane Kasprowy Hotel, Zakopane, Poland
Duration: 3 Jun 20187 Jun 2018
Conference number: 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10841 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018
Abbreviated titleICAISC 2018


  • Covariance matrix adaptation evolution strategy
  • Robotic flow shop scheduling

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