摘要
将遗传算法(GA)应用于飞机定检原位工作流程优化中。首先,建立原位工作流程优化模型;其次,提出"排序调整法"来保证个体对应解符合工序约束;最后采用精英选择算子。模拟退火算子和自适应机制对基本遗传算法(SGA)进行改进。仿真结果表明,改进遗传算法在最优解搜索能力上较SGA有明显提高,克服了其容易"早熟"的不足;优化后原位工作完成时间较优化前缩短19.78%,验证了GA在解决定检工作流程优化问题上的适用性。
Genetic algorithm（GA） is used to optimize plane＇s periodic maintenance primary workflow. Firstly, the model of pri- mary work is built. Secondly, the way of ＂adjusting the sequence＂ is proposed to ensure the solution of the individuals up to the limits of the work sequence. Finally, elitist operator, simulated annealing（SA） operator and adaptive mechanism are used to im- prove Simple Genetic Algorithm（SGA）. The simulation results demonstrate that, the improved GA is much stronger in best-solu- tion search ability than SGA, and it overcomes its deficiency of being easy to ＂precocity＂ ; after optimization the finish time of primary work is shorter 19.78% than before, and proves that GA is good for the optimization of primary periodic maintenance workflow.
出处
《计算机与现代化》
2012年第7期25-29,共5页
Computer and Modernization
关键词
GA
飞机定检
原位工作
流程优化模型
GA
plane＇ s periodic maintenance
primary work
work/low optimization model
