An Improved Particle Swarm Optimization Algorithm with Repair Procedure

In this paper a new particle swarm optimization algorithm called RPSO for solving high dimensional optimization problems is proposed and analyzed both in terms of their efficiency, the ability to avoid local optima and resistance to the problem of premature convergence. In RPSO, a repair procedure was introduced the aim of which was to determine new, better velocities for some particles, when their current velocities are inefficient. New velocities are the functions of previous and current velocities. The new algorithm was tested with a set of benchmark functions and the results were compared with those obtained through the standard PSO (SPSO) and IPSO. Simulation results show that new RPSO is faster and more effective than the standard PSO and IPSO.

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