Inequality constraint handling in genetic algorithms using a boundary simulation method

Abstract

Constraint handling is one of the major concerns when applying genetic algorithms (GAs) to solve constrained optimization problems. This paper proposes a boundary simulation method to address inequality constraints for GAs. This method can efficiently generate a feasible region boundary point set to approximately simulate the boundary of the feasible region. Based on the results of the boundary simulation method, GAs can start the genetic search from the boundary of the feasible region or the feasible region itself directly. Furthermore, a series of genetic operators that abandon or repair infeasible individuals produced during the search process is also proposed. The numerical experiments indicate that the proposed method can provide competitive results compared with other studies.