Multi-objective gravitational search algorithm based on decomposition

Abstract:

When the ideal frontier is discontinuous or inhomogeneous, the multi-objective evolutionary algorithm can’t solve multi-objective problems effectively by decomposition. In order to improve this situation, a novel multi-objective gravitational search algorithm based on decomposition (MOGSA／D) is proposed. In MOGSA／D, the multi-population serial strategy is good for the population study evolutionary information. According to shape prediction of ideal frontier, a suitable generation method of weight coefficient is selected. A pruning strategy is adopted to prune the solution set. Experimental results show that MOGSA has a good performance to solve multi-objective problems in comparison with other multi-objective optimization algorithms.