We propose an accelerated Difference-of-Convex algorithm (Boosted-DCA, or BDCA) with exact line search for efficiently solving Symmetric Eigenvalue Complementarity Problems (SEiCP). We first reformulate SEiCP to involve only symmetric positive definite matrices and introduce a logarithmic DC formulation. The proposed BDCA enhances the classical DCA with an exact line search based on the real roots of a binomial equation. Numerical experiments demonstrate that BDCA achieves significantly faster convergence and superior solutions compared to DCA, KNITRO, FILTERSD, and MATLAB’s FMINCON, particularly for large-scale and ill-conditioned problems.