The Concept on Nonlinear Modelling of Dynamic Objects Based on State Transition Algorithm and Genetic Programming

Bartczuk, Łukasz; Dziwiński, Piotr; Red’ko, Vladimir G.

doi:10.1007/978-3-319-59060-8_20

Cited by 7 publications

(1 citation statement)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…GEP, proposed by Ref. [26], is an evolutionary algorithm (EA) for effectively searching for accurate decision rules [27] . Compared with other EAs (e.g., genetic algorithm), the major difference in GEP lies in the form of the solution provided.…”

Section: Real-time Flow Shop Scheduling Approachmentioning

confidence: 99%

Real-Time Hybrid Flow Shop Scheduling Approach in Smart Manufacturing Environment

Chen

2021

Complex Syst. Model. Simul.

View full text Add to dashboard Cite

Smart manufacturing in the "Industry 4.0" strategy promotes the deep integration of manufacturing and information technologies, which makes the manufacturing system a ubiquitous environment. However, the real-time scheduling of such a manufacturing system is a challenge faced by many decision makers. To deal with this challenge, this study focuses on the real-time hybrid flow shop scheduling problem (HFSP). First, the characteristic of the hybrid flow shop in a smart manufacturing environment is analyzed, and its scheduling problem is described. Second, a real-time scheduling approach for the HFSP is proposed. The core module is to employ gene expression programming to construct a new and efficient scheduling rule according to the realtime status in the hybrid flow shop. With the scheduling rule, the priorities of the waiting job are calculated, and the job with the highest priority will be scheduled at this decision time point. A group of experiments are performed to prove the performance of the proposed approach. The numerical experiments show that the realtime scheduling approach outperforms other single-scheduling rules and the back-propagation neural network method in optimizing most objectives for different size instances. Therefore, the contribution of this study is the proposal of a real-time scheduling approach, which is an effective approach for real-time hybrid flow shop scheduling in a smart manufacturing environment.

show abstract

Section: Real-time Flow Shop Scheduling Approachmentioning

confidence: 99%