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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的开始时间、物料配送时间和物料在线边空间的存放区域,并提出了两作业间物料摆放位置调整的局部优化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。
Taking the aircraft moving production line as the actual background, the abstract of job assembly process scheduling is abstracted and extended for resource-constrained project scheduling. The actual factors such as material distribution and line storage decision-making and related capacity constraints are introduced. The goal of the mathematical model. Aiming at the model, a heuristic algorithm based on genetic algorithm is designed, which combines the knowledge generation algorithm and the local optimization search algorithm. Under the optimal global search ability of genetic algorithm, SCRDS algorithm is used to combine the operation sequence, resource constraints, distribution capabilities, line space and other factors to determine the start time, material delivery time and storage area of the line space in the line, and put forward A local optimization algorithm for adjusting the placement of materials between two jobs re-optimized the job start time and material delivery time to further shorten the total assembly schedule. The numerical experiment is carried out by using the standard case base, and the experimental results show the validity of the model and the algorithm.