摘要
针对解决以最大化加工收益和最小化碳排放总量为目标的柔性流水车间调度问题,提出一种改进的蚁群算法对其进行求解。对解空间使用3种邻域规则进行搜索,以提高解的质量;为提高解的多样性,采用1种自适应构造概率调整蚁群生成路径的方式;通过使用以帕累托规则为基础的多目标优化方法产生多个非支配解。通过数值实验,验证了所提出的改进蚁群算法的有效性——与传统的蚁群算法相比,所提出的方法在求解数量、质量上都具有明显优势。
To solve the scheduling problem in the flexible flow shop,to maximize the total early work and to minimize the total carbon emission,this paper proposes an improved ant colony algorithm.Three neighborhood rules are adopted to improve the quality of solutions,and one adaptive construction probability is used to adjust the ant colony generation path to improve the diversity of solutions.Moreover,a multi-objective optimization method is used based on Pareto rules to generate multiple non-dominated sets.Compared with the traditional ant colony algorithm,the proposed method has obvious advantages in terms of both quantity and quality.
作者
宋佳容
申雪峰
冯悦
陈鑫
SONG Jia-rong;SHEN Xue-feng;FENG Yue;CHEN Xin(School of Electronics&Information Engineering,Liaoning University of Technology,Jinzhou 121001,China)
出处
《辽宁工业大学学报（自然科学版）》
2023年第4期245-251,共7页
Journal of Liaoning University of Technology(Natural Science Edition)
基金
营口市企业·博士双创计划(2022-13)
辽宁省教育厅基本科研项目(LJKZZ20220085)。
