冷轧机组批量作业计划模型与算法

Model and algorithm of batch production scheduling of cold mill

中文关键词  冷轧  作业计划  多目标蚁群算法  Pareto非支配集

英文关键词  cold rolling  production scheduling  multi-objective ant colony optimization  Pareto non-domination solution

中文摘要

      针对编制冷轧机组作业计划受到钢卷宽度跳跃、入口厚度跳跃和出口厚度跳跃等多个工艺约束的问题, 把排产过程归纳为非对称双旅行商问题, 建立了冷轧机组生产作业计划的Pareto多目标模型. 提出了基于Pareto非支配集的自适应多目标蚁群算法, 利用自适应蚁群算法和Pareto非支配集思想, 综合考虑多个目标, 自适应地提供蚂蚁路径搜索参数, 并对得到的非支配解集对应路径更新信息素, 引导蚂蚁向最优解集方向搜索, 最终提供多个可行的批量作业计划, 根据生产要求从中选择合适的最优排产结果. 利用某冷轧薄板厂实际的生产数据进行仿真实验, 表明模型与算法在冷轧机组批量作业计划编制过程中具有可行性.

英文摘要

      In the production scheduling for a cold mill, a great number of constraints in production process have to be considered, such as the variations of material width and thickness at the entrance and exit of two continuous rolling steel coils. The scheduling process is transformed to an asymmetric two-traveling-salesman problem; and the Pareto-based multiobjective optimization model is established. A Pareto multi-objective adaptive-ant-colony algorithm based on the Pareto non-dominated set is introduced for solving the multi-objective problem. The Pareto non-dominated set is constructed by means of the adaptive-ant-colony algorithm and the Pareto optimization approach, which is used to guide ants to find the optimal solution. The parameters used to search a new path are updated automatically. The pheromones are changed automatically by considering all of the objectives and the process of searching path. Finally the scheduling solution is obtained by taking account of all objectives according to the requirements of production technologies. A simulation is conducted for a cold rolling mill, and the results indicate that the proposed algorithm is effective.