.png){kind=icon}
Return
Genetic algorithm parameter optimisation using Taguchi method for a flexible manufacturing system scheduling problem
.png){kind=icon}
PRE
AI
DOI：10.1080/00207543.2014.939244.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The flexible manufacturing system (FMS) scheduling problem is one of the most difficult NP-hard combinatorial optimisation problems. The exact solution of an FMS scheduling problem cannot be found within a reasonable amount of time, even for small size problems. Therefore, a metaheuristic algorithm is required to solve such a problem. The objective of this study is to develop a genetic algorithm (GA) approach to minimise makespan of the scheduling problem. A Taguchi orthogonal array is proposed instead of a full factorial experimental design for determining the parameters of the GA. The effects of the GA parameters on the minimum makespan values are determined and an analysis of variance is performed to investigate significance factors on the results.
Keywords:
Taguchi orthogonal arrays method
flexible manufacturing system scheduling
genetic algorithm
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.3
Papers:
1.1W
Citations:
3.7W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveShareSave
View more