面向门窗材的粒子群算法组框码垛优化OA

Customized door and window materials are characterized by diverse orders and complicated specifications.However,existing methods(such as artificial experience algorithms and the maximax space strategy)mainly focus on the single goal of maximizing space utilization,with little consideration for framing convenience and overall efficiency.This paper proposes a framing palletizing strategy based on a hybrid particle swarm optimization(PSO)algorithm to en-hance the overall efficiency of palletizing.Based on the processing characteristics before and after palletizing door/win-dow materials,a framing palletizing strategy is proposed to solve the problem of difficult workpiece position tracking.The particle encoding includes both position attributes and palletizing attributes of the materials,strengthening the hier-archical clustering effect of materials belonging to the same door/window unit.A multi-objective collaborative optimiza-tion function is established,with the weighted comprehensive efficiency of space utilization and framing convenience as the optimization goal.The simulation based on the actual orders of enterprises shows that compared with the traditional artificial experience algorithm and the maximax space strategy,the comprehensive efficiency of the proposed algorithm is improved by 17.11%and 17.34%,respectively,the framing convenience is 97.93%,and the space utilization rate is 80.48%.The field experiment verifies the effectiveness of the algorithm in actual production.The research shows that the proposed strategy not only ensures high space utilization,but also greatly improves the framing convenience,so as to effectively improve the overall efficiency of the production line.