资源空窗期及任务可拆分的资源投入问题研究

Resource Investment Problem with Activity Splitting and Resource Window

考虑飞机装配过程中任务可拆分及资源存在空窗期的两大特性,对飞机移动生产线资源投入问题进行模型与算法研究.针对部分任务存在已知拆分模式及拆分惩罚的情形,设计了求解该问题的改进遗传算法,对传统实数交叉操作进行优化,提出了基于染色体适应值的交叉方法,并在数值实验中对相关参数的取值范围进行了敏感性分析;同时,提出了基于任务开始时间选择概率的变异机制.对满足优化条件的任务调度方案,结合空窗期的位置,评判各可拆分任务可否通过选取新的拆分模式重新调度执行,对不同情形进行总结归纳,通过局部操作进一步降低目标资源量.数值实验表明:通过本文算法对求解带资源空窗期的任务不可拆分问题与基本问题的结果对比,得到任务数分别为10、16、30、60、90算例的目标值平均增量达到4.3%;对求解本文问题与任务不可拆分问题的结果对比,平均优化率达3.5%,证明了本文算法的有效性,同时证明将任务拆分纳入考虑资源空窗期的资源投入问题中,可提高问题求解的灵活性,从而获得较好的调度结果.

Considering the two characteristics of activity splitting and resource window in the process of aircraft assembly,the model and algorithm of Resource Investment Problem on aircraft mobile production line were studied.Aiming at the situation that some activities have known splitting mode and splitting punishment,an improved genetic algorithm for solving this problem was designed.The traditional real value crossover operation was optimized,and a crossover method based on chromosome fitness value was proposed.Sensitivity analysis was carried out on the range of values of the relevant parameters.A mutation mechanism based on the probability of selection of activity start time was also proposed.For a scheduling scheme that satisfies the optimization conditions,combined with the position of the resource window,after judging whether the splitting activities can be re-scheduled and executed by selecting a new splitting mode and summarizing the different situations,the target resources were further reduced by local operations.The numerical experiments show that,compared with the results of solving the problem of non-split activities with resource window and the basic problem,the average value of the target for the 10,16,30,60,90 activities is 4.3%.For the comparison between the results of solving this problem and the non-split problem,the average optimization rate is 3.5%,which proves the effectiveness of the algorithm.At the same time,it is proved that the activity splitting is included in the Resource Investment Problem considering the resource window,which can improve the flexibility of problem solving and obtain better scheduling results.