Particle Swarm Optimization Based on Genetic Operators for Nonlinear Integer Programming

In order to solve nonlinear integer programming which is widely used in engineering fields, a particle swarm optimization based on genetic operators is put forward. The integer restriction of problems is transformed by coding solutions. According to optimal solutions of population and individual, the new particle is updated by crossover, mutation and selection operators. After the numerical experiment of the algorithm, it is proved to be feasible and effective, especially in solving large-scale problems, it shows much better performance.