在对铜板带熔铸作业调度问题深入研究的基础上,建立了该问题最小化生产周期和总延时惩罚的多目标优化模型.结合基于分解的多目标进化算法框架和人工蜂群算法的邻域搜索策略,提出一种基于分解的人工蜂群算法对该模型进行优化求解,并结合实际问题的决策偏好,采用基于模糊集合理论的选优方法对非劣解进行排序.实例仿真表明,所提算法优于其他两种对比算法,能为调度人员优化决策提供有力依据.
Based on the studies of melting and casting scheduling problem in copper strip industry, a multi- objective optimization model for this problem's minimum production cycle and total delay punishment was established. By combining the framework of Multi Objective Evolutionary Algorithm/ Decomposition (MOEA/D) with the neigh- borhood search strategies of Artificial Bee Colony (ABC) algorithm, a Multi Objective Artificial Bee Colony/ De- composition (MOAIK2/D) algorithm was proposed to solve this model. Furthermore, a Pareto solutions sorting ap- proach based on fuzzy set theory was employed. The simulation result showed that the proposed MOABC/D algo- rithm was superior to the other two comparison algorithms and could provide evidences for the decision maker in scheduling optimization.