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工作流约束时间下焊接工艺质量迭代归约优化算法

罗智勇1,2,汪鹏1,尤波2,刘嘉辉1,苗世迪1

罗智勇1,2,汪鹏1,尤波2,刘嘉辉1,苗世迪1. 工作流约束时间下焊接工艺质量迭代归约优化算法[J]. 焊接学报, 2018, 39(8): 51-54. DOI: 10.12073/j.hjxb.2018390200
引用本文: 罗智勇1,2,汪鹏1,尤波2,刘嘉辉1,苗世迪1. 工作流约束时间下焊接工艺质量迭代归约优化算法[J]. 焊接学报, 2018, 39(8): 51-54. DOI: 10.12073/j.hjxb.2018390200
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LUO Zhiyong1,2, WANG Peng1, YOU Bo2, LIU Jiahui1, MIAO Shidi1. Iterative reduction optimization algorithm for quality of welding procedure based on constraint time[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(8): 51-54. DOI: 10.12073/j.hjxb.2018390200
Citation: LUO Zhiyong1,2, WANG Peng1, YOU Bo2, LIU Jiahui1, MIAO Shidi1. Iterative reduction optimization algorithm for quality of welding procedure based on constraint time[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(8): 51-54. DOI: 10.12073/j.hjxb.2018390200
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工作流约束时间下焊接工艺质量迭代归约优化算法

  • 1. 哈尔滨理工大学 计算机科学与技术学院, 哈尔滨 150080;
    2. 哈尔滨理工大学 机械动力工程学院, 哈尔滨 150080

基金项目: 国家自然科学基金青年项目（61403109）

Iterative reduction optimization algorithm for quality of welding procedure based on constraint time

  • 1. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China;
    2. School of Mechanical Engineering, Harbin University of Science and Technology, Harbin 150080, China

摘要

    摘要
  • 摘要: 针对焊接工艺流程约束时间下难于优化焊接质量的问题，提出了基于时间与质量相对平衡的迭代归约优化算法（iterative reduction optimization，IRO）.算法采用工作流模型，利用串行路径便于执行的特点，规范焊接各任务的活动区间，从而选择合适的服务；结合动态组合策略实现并行任务集合的虚拟归约，从而简化了原始工作流模型，通过层层迭代求解，找到最终的优化路径.结果表明，IRO算法能够实现约束时间下对焊接质量的优化；最后还分析了截止期与焊接任务数对算法性能的影响，得出通过改变对应的参数可提升算法优化效果的结论.
    Abstract: Aiming at optimizing the quality of welding production under constraint time, an iterative reduction optimization algorithm (IRO) based on the balance of time and quality is proposed. The algorithm adopts a workflow model, makes use of the serial path for easy implementation, standardizes the range of welding each task's activities, so as to select an appropriate service; combines a dynamic combination strategy to achieve a virtual reduction of the parallel task set, simplifies the original model, and finds the final optimization path by iterating through layers. The results of the test case show that IRO can achieve the optimization of the welding quality under constraint time. Finally, the influence of the deadline and the number of welding tasks on the performance of the algorithm is also analyzed. It is concluded that the optimization performance can be improved by changing the corresponding parameters.
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  • [1] De P, Dunner E J, Ghosh J B, et al. Complexity of the discrete time-cost trade-off problem for project networks[J]. Operations Research, 1997, 45(2):302-306.
    [2] Deldari Arash, Naghibzadeh Mahmoud, Abrishami Saeid. CCA:a deadline-constrained work-flow scheduling algorithm for multicore resources on the cloud[J]. Journal of Supercomputing, 2017, 73(2):756-781.
    [3] Pawel C. Run-time optimization and execution of distributed work-flow applications in the JEE-based Beesy Cluster environment[J]. The Journal of Supercomputing, 2013, 63(1):46-71.
    [4] 周万坤, 朱剑英, 孙志俊. 基于工作流技术的作业车间调度研究[J]. 南京航空航天大学学报, 2004, 36(1):125-129 Zhou W, Zhu J, Sun Z. Research on workflow technique based job-shop scheduling problem[J]. Journal o f Nanjing University of Aeronautics & Astronautics, 2004, 36(1):125-129
    [5] Luo Z Y, Wang P, You B, et al. Serial reduction optimization research of complex product workflow's accuracy under the time constraint[J]. Advances in Mechanical Engineering, 2016, 8(10):1-9.
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出版历程
  • 收稿日期:  2017-05-22

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