Open AccessApplication of Particle Swarm Optimization on Reliability Sampling Inspection Program for Success or Failure Product
Author(s) -
Yan Xiong,
Ning Cheng,
Yunzi Liu
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 - 10.1088/1742-6596/1861/1/012014
Subject(s) - particle swarm optimization , reliability (semiconductor) , heuristic , sampling (signal processing) , meta heuristic , reliability engineering , product (mathematics) , simplicity , computer science , mathematical optimization , field (mathematics) , swarm behaviour , multi swarm optimization , algorithm , engineering , mathematics , artificial intelligence , power (physics) , philosophy , physics , geometry , filter (signal processing) , quantum mechanics , epistemology , pure mathematics , computer vision
Reliability sampling inspection program for success or failure product is an intractable problem in the reliability test field. Meta-heuristic algorithm provides a new idea to solve the problem. Particle swarm algorithm is a new meta-heuristic algorithm in recent years, which has been widely used in many fields because of its simplicity but efficiency. In this paper, a reliability sampling inspection program model is developed to minimize the distance of risk. In addition, the mechanism of the particle swarm algorithm is expounded, and a case study reveals that the method in this paper is feasible and effective.