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。
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.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2017年第12期2573-2582,共10页
Journal of Beijing University of Aeronautics and Astronautics
基金
国家自然科学基金(61473211
71171130)~~
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
aircraft moving assembly line
material delivery
genetic algorithm
SCRDS algorithm
local optimization
