一种二维不规则零件优化排样算法

Hybrid Particle Swarm Optimization for Two Dimensional Irregular Parts Packing

将模拟退火算法和粒子群算法相结合,提出了一种基于模拟退火的粒子群算法。采用交叉和柯西变异运算,提高了算法的收敛速度和精度。将该算法应用于求解二维不规则零件排样问题,首先将二维不规则零件的排样问题转化为矩形件的排样问题,然后应用该算法进行优化求解,在求解过程中应用自适应调整策略对零件的排样位置进行微调。排样结果表明该算法是行之有效的。

A novel two dimensional irregular parts packing method using particle swarm optimization and simulated annealing is presented. The crossover operation and cauchy mutation operation are used to enhance the convergence performance and speed of the algorithm. The proposed algorithm is used to solve the packing problem of two-dimensional irregular parts. Firstly, the proposed method converts the packing problem of two dimensional irregular parts into rectangular parts packing problem by calculating the surrounding rectangle of irregular parts. Secondly, the algorithm is used to search for the optimal solution of the layout. The strategy of self-adaptive modulation is used to adjust the layout position of each rectangular part during the procedure of optimization. Solutions of two numerical examples show the effectiveness of the proposed algorithm.