Process planning and scheduling optimisation with alternative recipes

被引：4

作者：

Dziurzanski, Piotr ^{[1
]}

Zhao, Shuai ^{[1
]}

Scholze, Sebastian ^{[2
]}

Zilverberg, Albert ^{[2
]}

Krone, Karl ^{[3
]}

Indrusiak, Leandro Soares ^{[1
]}

机构：

[1] Univ York, Dept Comp Sci, Deramore Lane, York YO10 5GH, N Yorkshire, England

[2] Systemtech Bremen GmbH, Inst Angew, Wiener Str 1, D-28359 Bremen, Germany

[3] OAS AG, Caroline Herschel Str 1, D-28359 Bremen, Germany

来源：

AT-AUTOMATISIERUNGSTECHNIK | 2020年 / 68卷 / 02期

基金：

欧盟地平线“2020”;

关键词：

multi-objective job-shop scheduling; process manufacturing optimisation; multi-objective genetic algorithms; MULTIOBJECTIVE EVOLUTIONARY ALGORITHM;

D O I：

10.1515/auto-2019-0104

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：140 / 147

页数：8

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