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| Improved migrating bird algorithm for re-entrant hybrid flowshop scheduling problem with lot streaming |
Yabo LUO( ),Shaolong YU,Feng ZHANG*(),Cunrong LI |
| School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China |
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Abstract A re-entrant hybrid flowshop scheduling problem with lot streaming (RHFSP-LS) model was constructed in view of the difficulty of manual scheduling in array workshops to adapt to complex and variable production demands. An improved multi-objective migrating birds optimization algorithm was proposed for solving the model. A multi-objective migrating birds optimization algorithm based on non-dominated sorting, weighted sum, and external archive set was designed. The quality of the initial population was improved by using Logistic chaotic mapping and the NEH algorithm. A "sub-lot priority" + "batch priority" decoding strategy was proposed to enhance the algorithm’s solving capacity for special problems. A neighborhood search based on individual age was introduced to optimize the population’s neighborhood search direction. An escape mechanism combined with an external archive set was proposed to enhance the algorithm’s global search capability. The proposed strategies and algorithms were experimentally verified for the effectiveness and superiority in solving RHFSP-LS, ensuring an effective balance between the overall production cycle and the delivery deadlines of each process batch.
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Received: 25 September 2024
Published: 28 July 2025
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| Fund: 国家自然科学基金资助项目(51875430). |
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Corresponding Authors:
Feng ZHANG
E-mail: luoyabo@whut.edu.cn;zhangfengie@whut.edu.cn
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改进候鸟算法求解可重入混流车间批量流调度
鉴于阵列车间手工排产难以适应复杂多变的生产需求，构建可重入混合流水车间批量流调度问题（RHFSP-LS）模型，提出改进多目标候鸟优化算法进行求解. 设计基于非支配排序、加权总和与外部档案集的多目标候鸟优化算法. 利用Logistic混沌映射和NEH算法，提高了初始种群的质量. 提出“子批优先”+“批次优先”的解码策略，提升了算法对于特殊问题的求解能力. 提出基于个体年龄的邻域搜索，优化了种群的邻域搜索方向. 提出结合外部档案集的逃逸机制，提升了算法的全局搜索能力. 通过实验验证了所提策略及算法在解决RHFSP-LS上的有效性与优越性，保证了整体生产周期与各工艺批次交货期限的有效平衡.
关键词：
可重入混合流水车间,
批量流,
候鸟优化算法,
多目标优化,
生产调度
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