There are many engineering optimization problems whose optimal solution exists at the edge of the feasible space. For such active constrain problems, searching along the edge instead of the entire space can improve the search efficiency significantly without missing the optimum. We proposed an edge search strategy applied with Genetic Algorithms for power plant start-up scheduling problem. Our proposal has been proved theoretically and experimentally to solve active constrain problems with multimodal landscape efficiently.