Xiaofeng Lv
ABSTRACT
In order to solve the test optimization problem in aviation equipment test selection, a hybrid genetic particle swarm optimization (HGPSO) algorithm was improved on the basis of discrete particle swarm optimization (DPSO) algorithm. In the particle swarm optimization (PSO) algorithm, the cross and mutation operation of genetic algorithm is used to replace the updated formula of particle velocity and position. The method of crossover is that particles cross individual extremum and population extremum respectively, and the variation is linearly decreasing, so that particles can easily jump out of the local optimal solution and find the optimal solution. The simulation results show that the method works even better, the result of optimization is satisfied the requirements of testability of the system, which provide effective guidance for the selection of test optimization of complex systems.
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Index Terms
- Test optimization selection based on HGPSO Algorithm
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