Open AccessResearch on cloud forging resource service selection optimization based on genetic algorithm
Author(s) -
Kaijun Zhou,
Jichuan Hu,
Yuan Li,
Qian Wang,
Yifei Tong
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1812/1/012023
Subject(s) - cloud manufacturing , forging , cloud computing , computer science , resource (disambiguation) , scheduling (production processes) , genetic algorithm , service (business) , selection (genetic algorithm) , algorithm , distributed computing , manufacturing engineering , engineering , operations management , business , artificial intelligence , mechanical engineering , computer network , machine learning , marketing , operating system
As a concrete manifestation of “manufacturing as service”, cloud forging is a cross-integrated product of advanced manufacturing, information and emerging Internet of Things technology. To make full use of the manufacturing resources of cloud forging, it is of great importance to optimize the resource selection before scheduling. This research proposes a cloud forging resource service optimization strategy based on genetic algorithm. Taking into account the characteristics of cloud forging resource service optimization, sharing cost, interaction time, and service quality are selected as the three preferred indexes of cloud forging resource service, and these three indexes are quantified. The genetic algorithm is used to solve the cloud forging resource service optimization model, and the cloud forging resource service with the best performance is selected. Finally, an example is used to verify the effectiveness of the proposed method.