2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

考虑后续工序的择时综合调度算法

谢志强 张晓欢 辛宇 杨静

谢志强, 张晓欢, 辛宇, 杨静. 考虑后续工序的择时综合调度算法. 自动化学报, 2018, 44(2): 344-362. doi: 10.16383/j.aas.2018.c160562
引用本文: 谢志强, 张晓欢, 辛宇, 杨静. 考虑后续工序的择时综合调度算法. 自动化学报, 2018, 44(2): 344-362. doi: 10.16383/j.aas.2018.c160562
XIE Zhi-Qiang, ZHANG Xiao-Huan, XIN Yu, YANG Jing. Time-selective Integrated Scheduling Algorithm Considering Posterior Processes. ACTA AUTOMATICA SINICA, 2018, 44(2): 344-362. doi: 10.16383/j.aas.2018.c160562
Citation: XIE Zhi-Qiang, ZHANG Xiao-Huan, XIN Yu, YANG Jing. Time-selective Integrated Scheduling Algorithm Considering Posterior Processes. ACTA AUTOMATICA SINICA, 2018, 44(2): 344-362. doi: 10.16383/j.aas.2018.c160562

考虑后续工序的择时综合调度算法

doi: 10.16383/j.aas.2018.c160562
基金项目: 

国家自然科学基金 61370083

国家自然科学基金 61370086

高等学校博士学科点专项(博导类)科研基金 20122304110012

国家自然科学基金 61602133

黑龙江省博士后科研启动项目 LBH-Q13092

黑龙江省教育厅科技项目 12531105

国家自然科学基金 61672179

中国博士后资助项目 2016M591541

国家自然科学基金 61772160

黑龙江省博士后资助项目 LBH-Z15096

详细信息
    作者简介:

    张晓欢  哈尔滨理工大学博士研究生.主要研究方向为企业智能计算.E-mail:huanhuan291@126.com

    辛宇  哈尔滨理工大学计算机科学与技术学院讲师.2015年获哈尔滨工程大学计算机应用技术博士学位.主要研究方向为数据库与知识工程.E-mail:xinyu@hrbeu.edu.cn

    杨静  博士, 教授, CCF高级会员.主要研究方向为数据与知识工程, 数据挖掘, 隐私保护, 软件理论.E-mail:yangjing@hrbeu.edu.cn

    通讯作者:

    谢志强  博士, 教授, CCF高级会员.主要研究方向为企业智能计算与调度系统, 数据处理, 网络优化.本文通信作者.E-mail:xiezhiqiang@hrbust.edu.cn

Time-selective Integrated Scheduling Algorithm Considering Posterior Processes

Funds: 

National Natural Science Foundation of China 61370083

National Natural Science Foundation of China 61370086

Research Fund for the Doctoral Program of Higher Education 20122304110012

National Natural Science Foundation of China 61602133

the Heilongjiang Scientific Research foundation for the Postdoctoral LBH-Q13092

the Science and Technology Project of Heilongjiang Provincial Department of Education 12531105

National Natural Science Foundation of China 61672179

the China Postdoctoral Science Foundation 2016M591541

National Natural Science Foundation of China 61772160

the Heilongjiang Scientific Research Program for the Postdoctoral LBH-Z15096

More Information
    Author Bio:

     Ph. D. candidate at Harbin University of Science and Technology. Her main research interest is enterprise intelligence computing

     Lecturer at the College of Computer Science and Technology, Harbin University of Science and Technology. He received his Ph. D. degree from Harbin Engineering University in 2015. His research interest covers database and knowledge engineering

     Ph. D., professor, and senior member of China Computer Federation. Her research interest covers data and knowledge engineering, data mining, privacy protection, and computer software and theory

    Corresponding author: XIE Zhi-Qiang  Ph. D., professor, and senior member of China Computer Federation. His research interest covers intelligent computing and scheduling system, data processing and network optimization. Corresponding author of this paper
  • 摘要: 针对目前综合调度算法不能兼顾产品工艺树中并行工序的并行性和串行工序之间紧密度,影响调度结果的问题,提出考虑后续工序的择时综合调度算法.该算法提出工序序列排序策略,从工艺树的整体结构出发,将其划分成若干内部工序只具有串行关系的工序序列,并按路径长度从长到短的顺序确定其调度次序;提出择时调度策略和考虑后续工序策略,根据工艺树自身特点,从来自不同工序序列的并行工序的不同组合方案中,选择最接近调度目标的方案作为工序调度方案,若该工序调度方案不唯一,则在其中选择该工序加工开始时间最早的调度方案.该算法既保证了工序的并行处理,又提高了串行工序的紧密度,优化了综合调度的结果.最后通过实例说明本文算法对解决综合调试问题具有普遍意义.
    1)  本文责任编委 王红卫
  • 图  1  产品加工工艺树示例

    Fig.  1  The sample of processing tree of product

    图  2  调度思想示意图 1

    Fig.  2  Diagram 1 of the scheduling idea

    图  3  调度思想示意图 2

    Fig.  3  Diagram 2 of the scheduling idea

    图  4  产品$P$生产计划生成示意图

    Fig.  4  The production plan generates schematic of product $P$

    图  5  工序$i$择时调度示意图

    Fig.  5  The timing scheduling schematic of process $i$

    图  6  工序序列排序策略序列划分示意图

    Fig.  6  The schematic of sequence divided by operation sequence sorting strategy

    图  7  时间点$T_{1}$所涉及已调度工序

    Fig.  7  The scheduled process associated with the $T_{1}$

    图  8  处理工序$i$试调度后工序发生冲突示意图

    Fig.  8  The diagram of process conflict when process $i$ tried to scheduled

    图  9  产品工艺树

    Fig.  9  The processing tree of product

    图  10  仅使用择时策略在不同时间点调度工序$B_{1}$方案比较

    Fig.  10  Scheme comparison of Scheduling $B_{1}$ in different time when only use timing strategy

    图  11  采用考虑后续工序策略在不同时间点调度工序$B_{1}$方案比较

    Fig.  11  The comparison of scheme of scheduling $B_{1}$ in different time

    图  12  产品$A$的加工工艺树

    Fig.  12  The processing tree of product $A$

    图  13  使用文献[10]算法所得甘特图

    Fig.  13  Gantt chart using the algorithm of [10]

    图  14  使用文献[12]算法所得甘特图

    Fig.  14  Gantt chart using the algorithm of [12]

    图  15  使用本文算法所得甘特图

    Fig.  15  Gantt chart using the algorithm proposed

    表  1  综合调度问题参数表

    Table  1  Parameter list of integrated scheduling problem

    参数 含义
    $M_{i}$ 工序$i$的加工设备
    $T_{Si}$ 工序$i$的加工开始时间
    $T_{i}$ 工序$i$的加工用时
    $T_{Ei}$ 工序$i$的加工结束时间
    $T_{Mki}$ 调度工序$i$后第$k$台设备上当前加工完成时间, $1\leq k\leq m$
    $T_{Mi}$ 调度工序$i$后当前最晚加工完成的已调度工序加工完成时间
    $T_{Tij}$ 工序$i$的第$j$个"准调度时间点", $j\geq 1$
    $T_{Ti}$ 工序$i$的"准调度时间点"集合
    $F_{ij}$ 工序$i$在工艺树中的第$j$个紧前工序, $j\geq 1$
    $N_{if}$ 工序$i$在工艺树中的第$f$个紧后工序, $f\geq 1$
    $F_{Mi}$ 工序$i$在其加工设备上的紧前工序
    $N_{Mig}$ 工序$i$在其加工设备上的第$g$个后工序
    $N_{Qik}$ 工序$i$在其工序序列上的第$k$个后续工序
    下载: 导出CSV

    表  2  本文算法调度产品$A$过程

    Table  2  Scheduling the product $A$ by the algorithm proposed

    工序号 加工设备 准调度时间点 试调度方案加工总时间 后续工序静态调度时间 确定调度时间点 当前方案中每个工序调度时间点
    $A_{1}$ $M_3$ - - - 0 $A_{1}$: 0;
    $A_{2}$ $M_4$ - - - 2 $A_{1}$: 0, $A_{2}$: 2;
    $A_{10}$ $M_3$ - - - 4 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 4;
    $A_{11}$ $M_2$ - - - 6 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 4, $A_{11}$: 6;
    $A_{18}$ $M_1$ - - - 7 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 4, $A_{11}$: 6,
    $A_{18}$:7;
    $A_{15}$ $M_3$ - - - 8 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 4, $A_{11}$: 6,
    $A_{18}$:7, $A_{15}$: 8;
    $A_{21}$ $M_2$ - - - 11 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 4, $A_{11}$: 6,
    $A_{18}$:7, $A_{15}$: 8, $A_{21}$: 11;
    $A_{26}$ $M_3$ - - - 14 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 4, $A_{11}$: 6,
    $A_{18}$:7, $A_{15}$: 8, $A_{21}$: 11, $A_{26}$: 14;
    $A_{25}$ $M_2$ - - - 16 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 4, $A_{11}$: 6,
    $A_{18}$:7, $A_{15}$: 8, $A_{21}$: 11, $A_{26}$: 14,
    $A_{25}$: 16;
    $A_{28}$ $M_1$ - - - 17 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 4, $A_{11}$: 6,
    $A_{18}$:7, $A_{15}$: 8, $A_{21}$: 11, $A_{26}$: 14,
    $A_{25}$: 16, $A_{28}$: 17;
    $A_{3}$ $M_3$ 2|6|11|16 19|19|18|19 18|22|27|32 2 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$:7,
    $A_{18}$: 8, $A_{15}$: 9, $A_{21}$: 12, $A_{26}$: 15,
    $A_{25}$: 17, $A_{28}$: 18, $A_{3}$: 2;
    $A_{9}$ $M_4$ 5|19 19|22 19|32 5 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$:7,
    $A_{18}$: 8, $A_{15}$: 9, $A_{21}$: 12, $A_{26}$: 15,
    $A_{25}$: 17, $A_{28}$: 18, $A_{3}$: 2, $A_{9}$: 5;
    $A_{13}$ $M_3$ 8|12|17 20|19|19 18|22|27 8 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$:7,
    $A_{18}$: 8, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8;
    $A_{16}$ $M_2$ 10|16|19 20|21|22 18|24|27 10 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$:7,
    $A_{18}$: 8, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10;
    下载: 导出CSV

    表  3  本文算法调度产品$A$过程(续表 2)

    Table  3  Scheduling the product $A$ by the algorithm proposed (continued Table 2)

    工序号 加工设备 准调度时间点 试调度方案加工总时间 后续工序静态调度时间 确定调度时间点 当前方案中每个工序调度时间点
    $A_{23}$ $M_4$ 13|20 20|22 20|23 13 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 7,
    $A_{18}$: 8, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13;
    $A_{29}$ $M_1$ 15 20 18 15 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 7,
    $A_{18}$: 8, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15;
    $A_{5}$ $M_4$ 4|8|
    15|20
    20|20|
    20|21
    16|20|
    27|32
    4 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$:7,
    $A_{18}$: 8, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15,
    $A_{5}$: 4;
    $A_{7}$ $M_2$ 5|8|
    13|16|19
    20|21|
    23|21|22
    16|19|
    24|28|30
    5 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15,
    $A_{5}$: 4, $A_{7}$: 5;
    $A_{17}$ $M_1$ 8|10|18 20|20|20 16|18|26 8 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8;
    $A_{19}$ $M_4$ 9|15|20 20|20|22 16|22|27 9 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 9;
    $A_{22}$ $M_1$ 11|18 20|21 16|23 11 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 9,
    $A_{22}$: 11;
    $A_{20}$ $M_4$ 14|15|20 21|20|22 16|17|22 15 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 9,
    $A_{22}$: 11, $A_{20}$: 15;
    $A_{4}$ $M_2$ 2|8|9|
    13|16|19
    20|23|22|
    23|21|22
    13|19|20|
    24|28|30
    2 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 9,
    $A_{22}$: 11, $A_{20}$: 15, $A_{4}$: 2;
    下载: 导出CSV

    表  4  本文算法调度产品$A$过程(续表 3)

    Table  4  Scheduling the product $A$ by the algorithm proposed (continued Table 3)

    工序号 加工设备 准调度时间点 试调度方案加工总时间 后续工序静态调度时间 确定调度时间点 当前方案中每个工序调度时间点
    $A_{8}$ $M_1$ 5|9|10|
    14|18
    20|22|20|20|
    20
    13|17|18|
    22|26
    5 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 13, $A_{29}$: 15,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 9,
    $A_{22}$: 11, $A_{20}$: 15, $A_{4}$: 2, $A_{8}$: 5;
    $A_{14}$ $M_4$ 7|8|11|
    15|17|20
    26|20|20|
    22|22|24
    13|14|17|
    21|23|26
    8 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12,
    $A_{22}$: 14, $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 5,
    $A_{14}$: 8;
    $A_{27}$ $M_2$ 12|13|
    16|19
    21|22|
    20|21
    14|15|
    18|21
    16 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12,
    $A_{22}$: 14, $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 5,
    $A_{14}$: 8, $A_{27}$: 16;
    $A_{12}$ $M_1$ 5|7|
    9|10|
    17|20
    20|20|
    21|20|
    21|21
    13|15|
    17|18|
    25|28
    5 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12,
    $A_{22}$: 14, $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 6,
    $A_{14}$: 8, $A_{27}$: 16, $A_{12}$: 5;
    $A_{31}$ $M_2$ 6|8|
    9|13|
    16|18|19
    22|21|
    20|21|
    21|21|20
    13|15|
    16|20|
    23|25|
    26
    9 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12,
    $A_{22}$: 14, $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 6,
    $A_{14}$: 8, $A_{27}$: 16, $A_{12}$: 5, $A_{31}$: 9;
    $A_{24}$ $M_1$ 10|17|
    20
    20|24|
    24
    16|23|
    26
    10 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16, $A_{25}$: 18,
    $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5, $A_{13}$: 8,
    $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17, $A_{5}$: 4,
    $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12, $A_{22}$: 14,
    $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 6, $A_{14}$: 8, $A_{27}$: 16,
    $A_{12}$: 5, $A_{31}$: 9, $A_{24}$: 10;
    下载: 导出CSV

    表  5  本文算法调度产品$A$过程(续表 4)

    Table  5  Scheduling the product $A$ by the algorithm proposed (continued Table 4)

    工序号 加工设备 准调度时间点 试调度方案加工总时间 后续工序静态调度时间 确定调度时间点 当前方案中每个工序调度时间点
    $A_{30}$ $M_3$ 14|18 20|20 16|20 14 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 5, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12,
    $A_{22}$: 14, $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 6,
    $A_{14}$: 8, $A_{27}$: 16, $A_{12}$: 5, $A_{31}$: 9,
    $A_{24}$: 10, $A_{30}$: 14;
    $A_{6}$ $M_3$ 5|7|
    10|13|
    16|18
    20|20|
    21|20|
    21|20
    6|8|
    11|14|
    17|19
    5 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 6, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12,
    $A_{22}$: 14, $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 6,
    $A_{14}$: 8, $A_{27}$: 16, $A_{12}$: 5, $A_{31}$: 9,
    $A_{24}$: 10, $A_{30}$: 14, $A_{6}$: 5;
    $A_{32}$ $M_3$ 13|16|18 20|21|20 14|17|19 13 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 6, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12,
    $A_{22}$: 14, $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 6,
    $A_{14}$: 8, $A_{27}$: 16, $A_{12}$: 5, $A_{31}$: 9,
    $A_{24}$: 10, $A_{30}$: 14, $A_{6}$: 5,
    $A_{32}$: 13;
    $A_{33}$ $M_4$ 16|19|
    20
    20|21|
    21
    17|20|
    21
    16 $A_{1}$: 0, $A_{2}$: 2, $A_{10}$: 6, $A_{11}$: 8,
    $A_{18}$: 9, $A_{15}$: 10, $A_{21}$: 13, $A_{26}$: 16,
    $A_{25}$: 18, $A_{28}$: 19, $A_{3}$: 2, $A_{9}$: 5,
    $A_{13}$: 8, $A_{16}$: 10, $A_{23}$: 14, $A_{29}$: 17,
    $A_{5}$: 4, $A_{7}$: 5, $A_{17}$: 8, $A_{19}$: 12,
    $A_{22}$: 14, $A_{20}$: 17, $A_{4}$: 2, $A_{8}$: 6,
    $A_{14}$: 8, $A_{27}$: 16, $A_{12}$: 5, $A_{31}$: 9,
    $A_{24}$: 10, $A_{30}$: 14, $A_{6}$: 5, $A_{32}$: 13,
    $A_{33}$: 16;
    下载: 导出CSV
  • [1] 王大志, 刘士新, 郭希旺.求解总拖期时间最小化流水车间调度问题的多智能体进化算法.自动化学报, 2014, 40 (3):548-555 http://www.aas.net.cn/CN/abstract/abstract18320.shtml

    Wang Da-Zhi, Liu Shi-Xin, Guo Xi-Wang. A multi-agent evolutionary algorithm for solving total tardiness permutation flow-shop scheduling problem. Acta Automatica Sinica, 2014, 40 (3):548-555 http://www.aas.net.cn/CN/abstract/abstract18320.shtml
    [2] 黄敏, 付亚平, 王洪峰, 朱兵虎, 王兴伟.设备带有恶化特性的作业车间调度模型与算法.自动化学报, 2015, 41(3):551-558 http://www.aas.net.cn/CN/abstract/abstract18633.shtml

    Huang Min, Fu Ya-Ping, Wang Hong-Feng, Zhu Bing-Hu, Wang Xing-Wei. Job-shop scheduling model and algorithm with machine deterioration. Acta Automatica Sinica, 2015, 41 (3):551-558 http://www.aas.net.cn/CN/abstract/abstract18633.shtml
    [3] 王圣尧, 王凌, 许烨, 周刚.求解混合流水车间调度问题的分布估计算法.自动化学报, 2012, 38 (3):437-443 http://www.aas.net.cn/CN/abstract/abstract17695.shtml

    Wang Sheng-Yao, Wang Ling, Xu Ye, Zhou Gang. An estimation of distribution algorithm for solving hybrid flow-shop scheduling problem. Acta Automatica Sinica, 2012, 38 (3):437-443 http://www.aas.net.cn/CN/abstract/abstract17695.shtml
    [4] 贾文友, 江志斌, 李友.面向产品族优化时间窗下可重入批处理机调度.机械工程学报, 2015, 51 (12):192-201 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jxxb201512031&dbname=CJFD&dbcode=CJFQ

    Jia Wen-You, Jiang Zhi-Bin, Li You. Family-oriented to optimize scheduling problem of re-entrant batch processing machine with due window. Journal of Mechanical Engineering, 2015, 51 (12):192-201 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jxxb201512031&dbname=CJFD&dbcode=CJFQ
    [5] 张洁, 张朋, 刘国宝.基于两阶段蚁群算法的带非等效并行机的作业车间调度.机械工程学报, 2013, 49 (6):136-144 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jxxb201306020&dbname=CJFD&dbcode=CJFQ

    Zhang Jie, Zhang Peng, Liu Guo-Bao. Two-stage ant colony algorithm based job shop scheduling with unrelated parallel machines. Journal of Mechanical Engineering, 2013, 49 (6):136-144 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jxxb201306020&dbname=CJFD&dbcode=CJFQ
    [6] 羌磊, 肖田元.应用扩展贝叶斯进化算法求解混流装配调度问题.计算机集成制造系统, 2007, 13 (2):317-322 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jsjj200702017&dbname=CJFD&dbcode=CJFQ

    Qiang Lei, Xiao Tian-Yuan. Model extended BOA to solve hybrid assembly scheduling problems. Computer Integrated Manufacturing Systems, 2007, 13 (2):317-322 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jsjj200702017&dbname=CJFD&dbcode=CJFQ
    [7] 汪浩祥, 严洪森, 汪峥.知识化制造环境中基于双层Q学习的航空发动机自适应装配调度.计算机集成制造系统, 2014, 20(12):3000-3010 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jsjj201412010&dbname=CJFD&dbcode=CJFQ

    Wang Hao-Xiang, Yan Hong-Sen, Wang Zheng. Adaptive assembly scheduling of aero-engine based on double-layer Q-learning in knowledgeable manufacturing. Computer Integrated Manufacturing Systems, 2014, 20 (12):3000-3010 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jsjj201412010&dbname=CJFD&dbcode=CJFQ
    [8] 谢志强, 刘胜辉, 乔佩利.基于ACPM和BFSM的动态Job-Shop调度算法.计算机研究与发展, 2003, 40 (7):977-983 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jfyz200307011&dbname=CJFD&dbcode=CJFQ

    Xie Zhi-Qiang, Liu Sheng-Hui, Qiao Pei-Li. Dynamic job-shop scheduling algorithm based on ACPM and BFSM. Journal of Computer Research and Development, 2003, 40 (7):977-983 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jfyz200307011&dbname=CJFD&dbcode=CJFQ
    [9] 谢志强, 杨静, 杨光, 谭光宇.可动态生成具有优先级工序集的动态Job-Shop调度算法.计算机学报, 2008, 31 (3):502-508 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jsjx200803017&dbname=CJFD&dbcode=CJFQ

    Xie Zhi-Qiang, Yang Jing, Yang Guang, Tan Guang-Yu. Dynamic job-shop scheduling algorithm with dynamic set of operation having priority. Chinese Journal of Computers, 2008, 31 (3):502-508 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jsjx200803017&dbname=CJFD&dbcode=CJFQ
    [10] 谢志强, 杨静, 周勇, 张大力, 谭光宇.基于工序集的动态关键路径多产品制造调度算法.计算机学报, 2011, 34(2):406-412 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jsjx201102020&dbname=CJFD&dbcode=CJFQ

    Xie Zhi-Qiang, Yang Jing, Zhou Yong, Zhang Da-Li, Tan Guang-Yu. Dynamic critical paths multi-product manufacturing scheduling algorithm based on operation set. Chinese Journal of Computers, 2011, 34 (2):406-412 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jsjx201102020&dbname=CJFD&dbcode=CJFQ
    [11] 谢志强, 辛宇, 杨静.基于设备空闲事件驱动的综合调度算法.机械工程学报, 2011, 47 (11):139-147 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jxxb201111021&dbname=CJFD&dbcode=CJFQ

    Xie Zhi-Qiang, Xin Yu, Yang Jing. Integrated scheduling algorithm based on event driven by machines' idle. Journal of Mechanical Engineering, 2011, 47 (11):139-147 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=jxxb201111021&dbname=CJFD&dbcode=CJFQ
    [12] 谢志强, 辛宇, 杨静.可回退抢占的设备驱动综合调度算法.自动化学报, 2011, 37 (11):1332-1343 http://www.aas.net.cn/CN/abstract/abstract17623.shtml

    Xie Zhi-Qiang, Xin Yu, Yang Jing. Machine-driven integrated scheduling algorithm with rollback-preemptive. Acta Automatica Sinica, 2011, 37 (11):1332-1343 http://www.aas.net.cn/CN/abstract/abstract17623.shtml
    [13] Xie Z Q, Hao S Z, Ye G J, Tan G Y. A new algorithm for complex product flexible scheduling with constraint between jobs. Computers and Industrial Engineering, 2009, 57 (3):766-772 doi: 10.1016/j.cie.2009.02.004
    [14] Xie Z Q, Yang J, He Y J, Li Z M. An algorithm of simple multi-product scheduling problem with no-wait constraint between operations. Advanced Materials Research, 2010, 129-131:902-907 doi: 10.4028/www.scientific.net/AMR.129-131
    [15] Xie Z Q, Gui Z Y, Yang J. Integrated scheduling algorithm based on dynamic essential short path by device driver. Journal of Information and Computer Science, 2013, 10 (4):1075-1084 doi: 10.12733/issn.1548-7741
    [16] Xie Z Q, Yang J, He Y J, Ye G J. Dynamic integrated scheduling algorithm of complex multi-products with identical machines. Advanced Materials Research, 2010, 129-131:897-901 doi: 10.4028/www.scientific.net/AMR.129-131
    [17] Xie Z Q, He Y J, Liu C H, Yang J. Study on data storage of dynamic integrated scheduling. Procedia Engineering, 2012, 29:4017-4024 doi: 10.1016/j.proeng.2012.01.612
    [18] Xie Z Q, Wang P, Gui Z Y, Yang J. Integrated scheduling algorithm based on dynamic essential short path. Advances in Intelligent and Soft Computing. 2012, 169:709-715 doi: 10.1007/978-3-642-30223-7
  • 加载中
图(15) / 表(5)
计量
  • 文章访问数:  2900
  • HTML全文浏览量:  360
  • PDF下载量:  938
  • 被引次数: 0
出版历程
  • 收稿日期:  2016-08-19
  • 录用日期:  2017-05-04
  • 刊出日期:  2018-02-20

目录

    /

    返回文章
    返回