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作 者:王洪 吴立辉[3] 陈达 张洁 WANG Hong;WU Lihui;CHEN Da;ZHANG Jie(College of Mechanical Engineering,Donghua University,Shanghai,201620;Institute of Artificial Intelligence,Donghua University,Shanghai,201620;College of Mechanical Engineering,Shanghai Institute of Technology,Shanghai,201418)
机构地区:[1]东华大学机械工程学院,上海201620 [2]东华大学人工智能研究院,上海201620 [3]上海应用技术大学机械工程学院,上海201418
出 处:《中国机械工程》2024年第2期260-267,279,共9页China Mechanical Engineering
基 金:国家重点研发计划(2022YFB3305003)。
摘 要:针对多作业模式的半导体封装测试环节调度问题,以最小化最大完工时间为目标,提出了孪生人工蜂鸟算法。设计了孪生种群机制,通过构建双解码、孪生种群生成与协作方法,扩大解的搜索空间,提高初始解的质量,增加优化过程中解的多样性,进而提高求解精度。通过双向引导觅食策略,平衡算法多样性与收敛性,增强算法稳定性。通过构建四邻域搜索策略,增强算法局部优化能力。实验结果表明,该方法能有效缩短半导体封测环节的最大完工时间。In order to solve the scheduling problem of SAT in multi-operation mode,an artificial hummingbird algorithm with twin population was proposed with the goal of minimizing the maximum completion time.The twin population mechanism was designed to improve the solution accuracy.By double decoding,twin population generation and cooperation methods,the searching space for solutions was expanded,the quality of the initial population solution was improved,and the diversity of population solutions was increased in optimization processes.By the bidirectional-guiding foraging strategy,the relationship between algorithm diversity and convergence was balanced,and algorithm stability was enhanced.By the strategy of four-variable neighbor searching,the local optimization ability of the algorithm was enhanced.The test results show that the proposed method may effectively shorten the maximum completion time of the SAT.
关 键 词:生产调度 半导体封装测试 多作业模式 孪生人工蜂鸟算法
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程]
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