Scheduling of aerospace complex system test tasks based on multi-population genetic algorithm
In view of the large number of complex aerospace systems,the traditional test process design can only be manually customized,which is inefficient and not effectively optimized.At the same time,considering the urgent need for rapid testing of complex aerospace systems,a multi-objective genetic algorithm based on the method of au-tomatic generation of the aerospace test process was proposed.Under the premise of a clear set of test items,the test items were abstracted as discrete events,the total test time and test resource balance were taken as the optimi-zation goals,and many constraints of spacecraft testing were fully considered as the taboo items in the execution process of the genetic algorithm or variant contraindications.After the initial population was determined,the aero-space testing process was automatically generated and optimized.The simulation results of the numerical example showed that compared with the traditional semi-serial test method and single-objective optimization method under the same experimental conditions,the total test time or resource balance had been greatly improved.After further expanding the optimization objectives and constraints,the method could effectively improve the rapid response capa-bility and reliability of the aerospace complex system testing process.
process optimizationmulti-population genetic algorithmparallel task schedulingaerospace complex system test
万方数据
维普
