Abstract:

Aiming at the characteristics of multi-constraints condition and the deficiency of the existing automatic cotton blending, the improved genetic algorithm is applied to linear programming optimization problem. By improving generation strategy of the initial population, genetic operators and evolutionary convergence condition, constraint conditions of cotton blending will be fused dynamically with the evolution process so as to optimize automatic cotton blending. The experimental results show that the solution of the improved genetic algorithm is superior to that of the basic genetic algorithm and all index values of cotton blending are in line with the requirements of production technology. The cost of cotton blending can be reduced effectively under the premise of meeting the quality of mixed cotton. It also provides a new method and technical reference for the process design of cotton blending.

Key words: automatic cotton blending, cotton blending model, improved genetic algorithm, multi-constraints condition