Service Composition Optimization Method for Sewing Machine Cases Based on an Improved Multi-Objective Artificial Hummingbird Algorithm

In response to the low efficiency of collaborative processing of sewing machine cases at the part level in network collaborative manufacturing, this paper proposes a sewing machine cases manufacturing service composition optimization method based on an improved multi-objective artificial hummingbird...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Processes Ročník 13; číslo 8; s. 2433
Hlavní autoři: Shi, Gan, Liu, Shanhui, Shi, Keqiang, Zhu, Langze, Gao, Zhenjie, Zhang, Jiayue
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.08.2025
Témata:
Algorithms
Collaboration
Composition
Efficiency
Entrapment
Evolutionary computation
Field study
Genetic algorithms
Indicators
Investment analysis
Learning strategies
Manufacturing
Mathematical models
Methods
Multiple objective analysis
Optimization algorithms
Optimization models
Quality of service
Sewing
Sewing machines
ISSN:2227-9717, 2227-9717
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In response to the low efficiency of collaborative processing of sewing machine cases at the part level in network collaborative manufacturing, this paper proposes a sewing machine cases manufacturing service composition optimization method based on an improved multi-objective artificial hummingbird algorithm. The structure and production process of sewing machine cases are analyzed; a framework for service composition optimization in the sewing machine cases manufacturing service platform is established; the required manufacturing resource service composition is determined; and a dual-objective service composition optimization mathematical model that considers Quality of Service (QoS) indicators and flexibility indicators is constructed. Opposition-based learning strategies, roulette wheel selection strategies, and improved differential evolution strategies are embedded in the multi-objective artificial hummingbird algorithm, and the improved artificial hummingbird algorithm (ORAHA_DE) is used to solve the sewing machine cases manufacturing service composition optimization model. The experimental results show the effectiveness and superiority of this composition optimization method in solving the sewing machine cases manufacturing composition optimization problem while avoiding entrapment in a local optimum during the solution process, thereby achieving the composition optimization of sewing machine cases collaborative manufacturing services.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2227-9717
2227-9717
DOI:10.3390/pr13082433