TY - JOUR
T1 - Balance Study of Clothing Single-Piece Production Line Based on Dual-Population Genetic Algorithm 
AU - Yang , Ming-Ming
AU - Wu , Long
AU - Qi , Jing
AU - Ying , Bo-An
AU - Wang , Yue
JO - Journal of Fiber Bioengineering and Informatics
VL - 1
SP - 51
EP - 60
PY - 2024
DA - 2024/11
SN - 17
DO - http://doi.org/10.3993/jfbim03071
UR - https://global-sci.org/intro/article_detail/jfbi/23520.html
KW - Dual-population genetic algorithm, Balance optimisation, Garment sewing line, Simfactory software.
AB - <p style="text-align: justify;">Currently, line production is the mainstream production method for various clothing enterprises.
Therefore, optimising and improving the production line plays a crucial role in promoting the development
of manufacturing enterprises. To solve the problems of unbalanced operation time and low production line
balance rate of each workstation of the garment sewing production line, a multi-objective optimisation
mathematical model with the minimum smoothing index and the largest production line balance rate
was established, and the dual-population genetic algorithm was designed in the MATLAB environment.
The jeans (front piece) were used as an example to be simulated and verified in simulation software.
Achieve load balancing at workstations, save production costs, and eliminate overproduction between
jobs. The research results show that the smoothness index of the optimised production line has been
reduced from 20.89 to 8.43, and the production line balance rate has been increased from 77.57% to
89.06%, which meets the requirements of enterprise process planning and can deliver on time. This
verifies that the model proposed in this paper can effectively solve the production balance problem of a
single clothing production line.</p>