Abstract:

In order to  solve multi-objective optimization problems,a new memetic algorithm is proposed,which combines the global search ability of particle swarm optimization with synchronous local search heuristic for directed local fine-tuning.A new particle updating strategy is presented to deal with the problem of premature convergence and diversity maintenance in the swarm based upon the concept of fuzzy global-best.The proposed new features are verified to show their individual and combined effect in multi-objective optimization.The reactive power optimization result of IEEE14 node system by the new memetic shows that it has a good astringency and efficiency.

Key words: memetic algorithm, multi-objective optimization, particle swarm optimization