关键词: 集中下料, 零件样本, 零件分组, 优化

Abstract: To resolve the contradiction of time efficiency and material utilization ratio in Centralized Cutting Stock Problem (CCSP), a grouping optimization method based on parts samples was proposed. Based on the guiding role of parts samples, filtration grouping of most parts was accomplished. The formed parts group center was taken as its initial clustering center, and the remaining parts were completed by Hard C-Means (HCM). According to cutting stock combination characteristics of parts, the parts groups were recombined into several parts clusters. A dynamic compensation strategy based on parts clusters'material utilization ratio was adopted to adjust parts in different clusters. Combined each optimization result, the cutting plan of CCSP was obtained. Based on proposed method, a cutting system of bar stock was proposed, and compared with random grouping optimization without parts samples, the proposed method could obtain better cutting plan.

Key words: centralized cutting stock, parts samples, parts grouping, optimization