Optimization of one-dimensional wire cutting with variable length based on genetic ant colony algorithm

摘要

This paper presents an algorithm of one-dimensional wire cutting based on genetic algorithm and ant colony algorithm. Firstly, the dominant solution is screened out by genetic algorithm and transformed into the initial accumulation of pheromone in ant colony algorithm, and then the ant colony algorithm is used to adjust the dominant solution of genetic algorithm to obtain the approximate optimal solution. The experimental results show that the convergence rate of the fusion algorithm is faster than that of the ant colony algorithm, and the utilization rate of raw materials is higher than that of genetic algorithm. In addition, the optimal parameters are obtained by adjusting the experimental parameters of the fusion algorithm.