Name
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1515/auto-2019-0104 | AT-AUTOMATISIERUNGSTECHNIK |
Keywords | Field | DocType |
multi-objective job-shop scheduling,process manufacturing optimisation,multi-objective genetic algorithms | Industrial engineering,Scheduling (computing),Control engineering,Engineering | Journal |
Volume | Issue | ISSN |
68 | SP2 | 0178-2312 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Piotr Dziurzanski | 1 | 53 | 14.04 |
| Shuai Zhao | 2 | 0 | 0.34 |
| Sebastian Scholze | 3 | 22 | 7.98 |
| Albert Zilverberg | 4 | 0 | 0.34 |
| Karl Krone | 5 | 0 | 0.34 |
| Leandro Soares Indrusiak | 6 | 486 | 92.68 |