Epsilon constrained method for constrained multiobjective optimization problems
Zhixiang Yang, Xinye Cai, Zhun Fan · 2014
In this paper, the ε constrained method and Adaptive operator selection (AOS) are used in Multiobjective evolutionary algorithm based on decomposition (MOEA/D). The ε constrained method is an algorithm transformation method, which can convert algorithms for unconstrained problems to algorithms for constrained problems using the ε level comparison, which compares search points based on the pair of objective value and constraint violation of them. AOS is used to determine the application rates of different operators in an online manner based on their recent performances within an optimization process. The experimental results show our proposed approach for multiobjective constrained optimization is very competitive compared with other state-of-art algorithms.