Open AccessA Closed-Loop Assembly Network Optimization Based on Chance Constraint with Robust Approximation
Author(s) -
Dongyuan Wei,
Yue Wang,
Xinchao Li,
Shan Lu
Publication year - 2022
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 - 10.1088/1742-6596/2203/1/012060
Subject(s) - mathematical optimization , robust optimization , scheduling (production processes) , constraint (computer aided design) , computer science , set (abstract data type) , upper and lower bounds , algorithm , mathematics , mathematical analysis , geometry , programming language
In this paper, an optimization algorithm of forward-reverse cyclic assembly network under uncertainty is studied. A chance constrained algorithm based on robust approximation is adopted, in which the size of uncertain set is used to describe the violation probability of constraint. Further, some parameters are set to describe the confidence probability of the model. By implementing the proposed algorithm, we can reduce the manufacturing cost of the final forward-reverse cycle assembly network by 3.17% while ensuring a certain confidence probability, and relax the lower bound of the probability of the model, which makes the model more adaptable. By calculating the scheduling data and comparing with flexible robust optimization, the effectiveness of the algorithm is proved.