A Multi-objective Optimization Algorithm Based on Differential Evolution with the Bidirectional-search Mechanism
Yun Bo Guo · Electronic Science and Technology · 2012
In order to avoid the situation of falling into local optimum when solving the Multi-objective Optimization Problem(MOP) with Differential Evolution Algorithm(DE),we design a bidirectional search mechanism which can improve the ability of local search of the DE and reduce the risk of local optimum,as well as make the Pareto fronts more evenly distributed.Experimental results show that the proposed method is more efficient than similar algorithms such as NSGA-II with better precision and distribution of Pareto optimal solution.