论文标题
用于飞机重型维护的资源约束项目调度问题的遗传算法
Genetic algorithms for the resource-constrained project scheduling problem in aircraft heavy maintenance
论文作者
论文摘要
由于飞机重型维护（AHM）的一系列相互关联的活动集合，许多航空公司必须处理大量的飞机维护停机时间。 AHM中的调度问题被视为NP硬性问题。使用精确的算法可能是耗时的，甚至是不可行的。本文提出了用于解决AHM中资源约束项目调度问题（RCPSP）的遗传算法。该研究的目的是最大程度地减少维护计划的制造商。拟议的算法应用了五个启发式调度规则，以基于活动列表形成生成初始人群。 rcpspearllaw的开始时间（EST）和工作组的资源分配方法以及最早的开始时间（西） - 用于评估健身价值。在选择过程中应用了精英和轮盘旋轮方法。然后，通过交叉和突变操作迭代地改进了活动列表的序列。结果表明，在计算时间和资源分配方面，所提出的算法与现有解决方案相比有效地性能。
Due to complex sets of interrelated activities in aircraft heavy maintenance (AHM), many airlines have to deal with substantial aircraft maintenance downtime. The scheduling problem in AHM is regarded as an NP-hard problem. Using exact algorithms can be time-consuming or even infeasible. This article proposes genetic algorithms for solving the resource-constrained project scheduling problem (RCPSP) in AHM. The objective of the study was to minimise the makespan of the maintenance plan. The proposed algorithms applied five heuristic dispatching rules to generate an initial population based on activity list formation. Resource allocation methods for RCPSPearliest start time (EST) and workgroup and earliest start time (WEST)-were used to evaluate the fitness value. The elitist and roulette wheel methods were applied in the selection process. The sequences of the activity lists were then iteratively improved by crossover and mutation operations. The results show that the proposed algorithms perform efficiently compared to the existing solutions in terms of computational time and resource allocation.
