Process Planning and Scheduling Optimisation with Alternative Recipes

Piotr Dziurzanski, Shuai Zhao, Sebastian Scholze, Albert Zilverberg, Karl Krone, Leandro Soares Indrusiak

Research output: Contribution to journalArticlepeer-review


This paper considers an application of a new variant of a multi-objective flexible job-shop scheduling problem, featuring multisubset selection of manufactured recipes, to a real-world chemical plant. The problem is optimised using a multi-objective genetic algorithm with customised mutation and elitism operators that minimises both the total production time and the produced commodity surplus. The algorithm evaluation is performed with both random and historic manufacturing orders. The latter demonstrated that the proposed system can lead to more than 10\% makespan improvements in comparison with human operators.
Original languageEnglish
Journalat - Automatisierungstechnik
Issue number2
Early online date22 Jan 2020
Publication statusPublished - 25 Feb 2020

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

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