A Multi-objective optimization based on adaptive environmental selection

There are many defects for PSO to solve multi-objective optimization problems. For example, the population of particles will lose activity when algorithm falls into local optimum, and there is no good method to solve the problem of the select of the global optimal value for the population and the history of individual optimal value. This paper introduces SPEA2 environmental selection and pair selection strategy to algorithm to solve the problem of the select of the global optimal value for the population and the history of individual optimal value, and in order to solve the active of population particles problem this paper will use the adaptive principle to change the method of calculating speed weight. This paper will through the simulation experiment of four classical test functions and the planning of robot path to verify the performance of the algorithm what is changed.