This study presents a numerical method for the optimal control problem with equilibrium constraints (OCPEC). It is extremely difficult to solve OCPEC owing to the absence of constraint regularity and strictly feasible interior points. To solve OCPEC efficiently, we first relax the discretized OCPEC to recover the constraint regularity and then map its Karush-Kuhn-Tucker (KKT) conditions into a parameterized system of equations. Subsequently, we solve the parameterized system using a novel two-stage solution method called the non-interior-point continuation method. In the first stage, a non-interior-point method is employed to find an initial solution, which solves the parameterized system using Newton's method and globalizes convergence using a dedicated merit function. In the second stage, a predictor-corrector continuation method is utilized to track the solution trajectory as a function of the parameter, starting at the initial solution. The proposed method regularizes the KKT matrix and does not enforce iterates to remain in the feasible interior, which mitigates the numerical difficulties in solving OCPEC. Convergence properties are analyzed under certain assumptions. Numerical experiments demonstrate that the proposed method can solve OCPEC while demanding remarkably less computation time than the interior-point method. (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).