Multi-objective evolutionary algorithm that diversifies population by its density (MODdEA) solve multi-objective optimization problem according to the non-dominated sorting information and spatial density information

the algorithm has a good performance in the comparison with other multi-objective evolutionary algorithm.In this paper

we propose an improved multi-objective evolutionary algorithm MODdEA + based on MODdEA.Firstly

we propose a operator named clone operator based on the partition mechanism in search space

this operator could not only improve the global search capabilities in the early stage of evolution

but also enhance the local refinement capabilities in the late stage of evolution;secondly

we introduce a evaluation strategy which evaluate the individuals in Pareto information list based on the dominate and dominated information

this strategy provide a more accurate sorting result;finally

we improve the mutation operator in order to reduce the probability of overstep of the boundary.To demonstrate the effectiveness of the improved algorithm

we compare it with MODdEA on multiple testing problems

the experimental results show that the improved algorithm's solving quality is much better than the original algorithm's.