Title :
Research on Test Paper Auto-generating Based on Improved Particle Swarm Optimization
Author :
Chong Zhang;Jing Zhang
Author_Institution :
Tianjin Polytech. Univ., Tianjin, China
Abstract :
The existing algorithm of generating test paper has the problem of low efficiency and slow convergence rate, etc. Improved particle swarm algorithm for test paper auto-generating is proposed on the basic of the particle swarm optimization algorithm and improved genetic algorithm. The algorithm uses greedy algorithm to optimize the initial population. The crossover and mutation operator of genetic algorithm are used to avoid the local convergence of population during the process of iteration. Experimental results show that the improved particle swarm optimization algorithm can applied to auto-generating test paper, which has faster speed and higher success rate.
Keywords :
"Parallel architectures","Programming"
Conference_Titel :
Parallel Architectures, Algorithms and Programming (PAAP), 2015 Seventh International Symposium on
DOI :
10.1109/PAAP.2015.27