In order to strengthen the diversity of Pareto sets obtained by multi-objective optimization algorithms and balance the exploration and exploitation of the algorithms

a cellular multi-objective particle swarm optimization algorithm based on multi-strategy differential evolution (MPSOCell) is proposed.This algorithm is composed by integrating the cellular automate mechanism into the basic particle swarm optimization algorithm

and it is aimed at promoting the communication and information transmission among the particles.To avoid the local convergence caused by the fast flying speed of particles

a strategy used to limit the flying speed is designed;to strengthen the disturbance to the particles

a multi-strategy differential evolution operator is also brought into the algorithm.The experiments demonstrate that MPSOCell has better performance in terms of convergence and diversity.