Process Planning and Scheduling Optimisation with Alternative Recipes

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

doi:10.1515/auto-2019-0104

Process Planning and Scheduling Optimisation with Alternative Recipes

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

Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

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 language	English
Journal	at - Automatisierungstechnik
Volume	68
Issue number	2
Early online date	22 Jan 2020
DOIs	https://doi.org/10.1515/auto-2019-0104
Publication status	Published - 25 Feb 2020

Bibliographical note

Keywords

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

Access to Document

10.1515/auto-2019-0104

[at - Automatisierungstechnik] Process planning and scheduling optimisation with alternative recipes (1)
© 2020 Walter de Gruyter GmbH, Berlin/Boston. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details
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Cite this

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