• 更多栏目

    林林

    • 教授     博士生导师   硕士生导师
    • 主要任职:软件学院、大连理工大学-立命馆大学国际信息与软件学院副院长
    • 性别:男
    • 毕业院校:日本早稻田大学
    • 学位:博士
    • 所在单位:软件学院、国际信息与软件学院
    • 学科:软件工程
    • 办公地点:开发区校区 信息楼305
    • 电子邮箱:lin@dlut.edu.cn

    访问量:

    开通时间:..

    最后更新时间:..

    Recent Advances in Multiobjective Genetic Algorithms for Manufacturing Scheduling Problems

    点击次数:

    论文类型:会议论文

    发表时间:2014-07-25

    收录刊物:EI、Scopus

    卷号:281

    页面范围:815-831

    摘要:Manufacturing scheduling is one of the important and complex combinatorial optimization problems in manufacturing system, where it can have a major impact on the productivity of a production process. Moreover, most of scheduling problems fall into the class of NP-hard combinatorial problems. In this paper, we concern with the design of multiobjective genetic algorithms (MOGAs) to solve a variety of manufacturing scheduling problems. In particularly, the fitness assignment mechanism and evolutionary representations as well as the hybrid evolutionary operations are introduced. Also, several applications of EAs to the different types of manufacturing scheduling problems are illustrated. Through a variety of numerical experiments, the effectiveness of these hybrid genetic algorithms (HGAs) in the widely applications of manufacturing scheduling problems are demonstrated. This paper also summarizes a classification of scheduling problems and the design way of GAs for the different types of manufacturing scheduling problems in which we apply GAs to a multiobjective flexible job-shop scheduling problem (MoFJSP; operation sequencing with resources assignment) and multiobjective assembly line balancing models (MoALB; shipments grouping and assignment). It is useful to guide how to investigate an effective GA for the practical manufacturing scheduling problems. ? Springer-Verlag Berlin Heidelberg 2014.