学术论文

      基于聚类--约束满足算法的钢管入库优化决策模型

      Optimization model of steel tube location decision based on clustering and constraint satisfaction algorithm

      摘要:
      针对钢管入库优化决策问题,建立了问题的约束满足优化模型,并通过对垛高和钢管堆放规则的分析,提出了基于聚类和约束满足技术的两阶段求解算法。算法在第一阶段采用聚类的方式对待入库的钢管按照多重属性进行分组;在第二阶段利用约束满足技术对于每组钢管分别指派垛位及其在垛位上的具体位置,并通过约束传播动态缩减问题的搜索空间。最后将算法与经典的BFD ( best fit deceasing)算法进行实验结果对比。实验结果表明,算法能够在保证倒垛次数最小的前提下,有效减少垛位数并具有良好的垛位利用率,模型及算法可行、有效。
      Abstract:
      A constraint satisfaction optimization model was presented to deal with the optimization decision problem about the steel tube location. Through the analysis of stack height and the piling rules of steel tubes, a two-stage algorithm was given based on cluste-ring and constraint satisfaction technology. In the first stage, steel tubes to be put into storage are grouped by clustering-based approach according to their multiple attributes. In the second stage, by using constraint satisfaction technology, the specific location of steel tubes in each group is assigned, and the search space of the problem is dynamically shrunk through constraint propagation. Finally, this algorithm was compared with the classical BFD ( best fit deceasing) algorithm through experiments. Experimental results demon-strate that, in the premise of minimizing stacking operations, the algorithm can effectively reduce the quantity of stacks and achieve a well-performed utilization rate of stacks. And thus the results verify the feasibility and effectiveness of the model and algorithm.
      Author: DONG Guang-jing SHI Can-tao LI Tie-ke WANG Bai-lin
      作者单位: 北京科技大学东凌经济管理学院,北京100083; 钢铁生产制造执行系统技术教育部工程研究中心,北京100083
      刊 名: 北京科技大学学报 ISTICEIPKU
      年,卷(期): 2014, (1)
      分类号: TP29
      机标分类号: TP3 TP1
      在线出版日期: 2014年2月16日
      基金项目: 教育部博士学科点专项科研基金资助项目,中央高校基本科研业务费专项资金资助项目