A Modified Multi Objective Optimization Based on Brain Storm Optimization Algorithm
In recent years, many evolutionary algorithms and population based algorithms have been developed for solving multi objective optimization problems. In this paper, A new Multi objective optimization algorithm Modified Multiobjective Brain Storm Optimization (MMBSO) algorithm is proposed. The clustering strategy acts directly in the objective space instead of in the solution space and suggests potential Pareto dominance areas in the next iteration. A Density Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise (DBSCAN) clustering and Differential Evolution (DE) mutations are used to improve the performance of MBSO. A group of multi objective problems with different characteristics were tested to validate the usefulness and effectiveness of the proposed algorithm. Experimental results show that MMBSO is a very promising algorithm for solving these tested multi objective problems.
ICSI