Extending the Push and Pull Search Framework with Boundary Search for Constrained Multi-Objective Optimization

adding feasibility to the existing multiple objective challenge. Further, the presence of complex constraints poses a significant challenge to multi-objective evolutionary algorithms. A recently proposed biphasic multi-objective evolutionary framework for constrained multi-objective optimization problems is the Push and Pull Search framework. This framework benefits from a strong exploration of the constrained landscape during the search for the unconstrained Pareto-Front during the first phase. The work herein extends the Push and Pull Search framework, extending landscape information gathering in the push phase; adding a binary search of the feasible and infeasible regions and creating a suitably diverse population and improved initialization for the push phase.