A scheduling algorithm of particle swarm optimization with segmental pheromone heuristics

Coping with such disadvantages of particle swarm optimization(PSO) algorithm being easy to run into local optima for combination optimization problems, the method that particle swarm optimization infused with mechanism of ant colony optimization(ACO) is proposed. We adopt gene section decomposition for solving classical scheduling problems of permutation flow shop. The function of positive feedback of pheromone is introduced to accelerate local search for PSO. Simulation results verify the feasibility and effectiveness of the proposed algorithm.