摘要
针对生产车间中需要同时考虑减少生产时间、确保加工质量以及通过减少能耗而降低生产费用的需求,建立以完工时间、空闲时间、加工质量和机器能耗为目标的多目标混合流水车间调度模型,提出一种基于直觉模糊集相似度的最佳觅食算法.为有效求解此问题,提出基于Largest Order Value规则的双层整数编码方式,在机器层编码部分采用权重法来计算机器的选择概率.针对多目标优化,提出直觉模糊集相似度的解比较策略,采用直觉模糊集相似度的大小衡量Pareto解与理想解的相似程度,判断Pareto解的优劣.通过测试实例和实际案例,验证本算法求解多目标混合流水车间调度问题的有效性和可行性.
To meet the demand of reducing production time, ensuring processing quality, and reducing production cost through reducing energy consumption in the production shop, a multi-objective hybrid flow shop scheduling(MOHFS) model is established with the objectives of completion time, idle time, processing quality and machine energy consumption. An optimal foraging algorithm based on the intuitionistic fuzzy sets similarity is proposed to solve MOHFS problem. To solve this problem effectively, a two-layer integer coding method based on the Largest Order Value rule is proposed, and the weighting method is used to calculate the selection probability of the machine in machine layer coding. For multi-objective optimization, a solution comparative strategy based on the intuitionistic fuzzy set similarity value is proposed. This strategy is used to judge the Pareto solution through measuring the similarity between the Pareto solution and the ideal solution. With the test examples and actual case, the effectiveness and feasibility of the algorithm for solving multi-objective hybrid flow shop scheduling problem are verified.
作者
杜士卿
朱光宇
徐文婕
DU Shiqing;ZHU Guangyu;XU Wenjie(College of Mechanical Engineering and Automation,Fuzhou University,Fuzhou,Fujian 350108,China)
出处
《福州大学学报（自然科学版）》
CAS
北大核心
2020年第3期325-332,共8页
Journal of Fuzhou University(Natural Science Edition)
基金
工信部2016智能制造综合标准化与新模式应用资助项目(工信部联装(2016)213号)
福建省客车及特种车辆研发协同创新中心基金资助项目(2016BJC011)
福州市科技局基金资助项目(2017-G-71)。
关键词
最佳觅食算法
双层整数编码
直觉模糊集相似度
多目标优化
混合流水车间调度
optimal foraging algorithm
two-layer integer coding
intuitionistic fuzzy sets similarity
multi-objective optimization
hybrid flow shop scheduling
