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Solving the Multi-objective Flexible Job-Shop Scheduling Problem with Alternative Recipes for a Chemical Production Process

  • Piotr DziurzanskiEmail author
  • Shuai Zhao
  • Jerry Swan
  • Leandro Soares Indrusiak
  • Sebastian Scholze
  • Karl Krone
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11454)

Abstract

This paper considers a new variant of a multi-objective flexible job-shop scheduling problem, featuring multisubset selection of manufactured recipes. We propose a novel associated chromosome encoding and customise the classic MOEA/D multi-objective genetic algorithm with new genetic operators. The applicability of the proposed approach is evaluated experimentally and showed to outperform typical multi-objective genetic algorithms. The problem variant is motivated by real-world manufacturing in a chemical plant and is applicable to other plants that manufacture goods using alternative recipes.

Keywords

Multi-objective job-shop scheduling Process manufacturing optimisation Multi-objective genetic algorithms 

Notes

Acknowledgement

The authors acknowledge the support of the EU H2020 SAFIRE project (Ref. 723634).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Piotr Dziurzanski
    • 1
    Email author
  • Shuai Zhao
    • 1
  • Jerry Swan
    • 1
  • Leandro Soares Indrusiak
    • 1
  • Sebastian Scholze
    • 2
  • Karl Krone
    • 3
  1. 1.Department of Computer ScienceUniversity of YorkYorkUK
  2. 2.Institut fur Angewandte Systemtechnik Bremen GmbHBremenGermany
  3. 3.OAS AGBremenGermany

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