北京航空航天大学学报 ›› 2017, Vol. 43 ›› Issue (12): 2573-2582.doi: 10.13700/j.bh.1001-5965.2016.0932

• 论文 • 上一篇    

考虑物料配送的飞机移动生产线调度问题优化

胡鑫铭, 陆志强   

  1. 同济大学 机械与能源工程学院, 上海 201804
  • 收稿日期:2016-12-12 修回日期:2017-01-20 出版日期:2017-12-20 发布日期:2017-03-16
  • 通讯作者: 陆志强 E-mail:zhiqianglu@tongji.edu.cn
  • 作者简介:胡鑫铭,男,硕士研究生。主要研究方向:生产调度的建模与优化;陆志强,男,教授,博士生导师。主要研究方向:物流与供应链建模与优化、生产工程等。
  • 基金资助:
    国家自然科学基金(61473211,71171130)

Optimization of aircraft moving assembly line scheduling problem considering material delivery

HU Xinming, LU Zhiqiang   

  1. School of Mechanical Engineering, Tongji University, Shanghai 201804, China
  • Received:2016-12-12 Revised:2017-01-20 Online:2017-12-20 Published:2017-03-16
  • Supported by:
    National Natural Science Foundation of China (61473211,71171130)

摘要: 以飞机移动生产线为实际背景,将作业装配过程调度抽象为资源受限项目调度问题并进行了扩展,引入物料配送与线边存储决策,以及相关能力约束等实际因素,建立了以装配总工期最小化为目标的数学模型。针对模型,设计了一种以遗传算法为框架的启发式算法,其中结合了解生成算法和局部优化搜索算法。在遗传算法较优的全局搜索能力下,通过SCRDS算法综合作业顺序、资源约束、配送能力、线边空间等因素,联合决策作业开始时间、物料配送时间和物料在线边空间的存储位置,提出了两作业间物料摆放位置调整的局部优化搜索算法,对作业开始时间和物料配送时间进行再优化,进一步缩短了装配总工期。利用标准算例库进行了数值实验,实验结果证明了模型与算法的有效性。

关键词: 飞机移动生产线, 物料配送, 遗传算法, SCRDS算法, 局部优化

Abstract: This paper abstracted the scheduling of assembly process as a resource-constrained project scheduling problem in the background of aircraft moving assembly line, and decisions about material delivery and the storage of line-side material were introduced considering the capabilities, constraints and other practical factors. An integrating mathematical model with the objective of minimizing the makespan was established. A heuristic algorithm was proposed based on genetic algorithm framework, combining with solution generation algorithm and local optimization search algorithm. With the global searching advantages of genetic algorithm, a joint decision of start time, material delivery time and material storage position in line-side space for each job was made taking into account job sequence, resource constraints, delivery capability, line-side space and other factors through SCRDS algorithm. On this basis, a local optimization algorithm aiming at adjusting line-side material positions between two jobs was proposed to re-optimize the start time and material delivery time of jobs, which decreases the project duration further. Numerical experiments were carried out by using a standard example library and the results proved the validity of the model and algorithm.

Key words: aircraft moving assembly line, material delivery, genetic algorithm, SCRDS algorithm, local optimization

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