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In this paper, we are interested in developing an acceleratedDifference-of-Convex (DC) programming algorithm based on the exact line searchfor efficiently solving the Symmetric Eigenvalue Complementarity Problem(SEiCP) and Symmetric Quadratic Eigenvalue Complementarity Problem (SQEiCP). Wefirst proved that any SEiCP is equivalent to SEiCP with symmetric positivedefinite matrices only. Then, we established DC programming formulations fortwo equivalent formulations of SEiCP (namely, the logarithmic formulation andthe quadratic formulation), and proposed the accelerated DC algorithm (BDCA) bycombining the classical DCA with inexpensive exact line search by finding realroots of a binomial for acceleration. We demonstrated the equivalence betweenSQEiCP and SEiCP, and extended BDCA to SQEiCP. Numerical simulations of theproposed BDCA and DCA against KNITRO, FILTERED and MATLAB FMINCON for SEiCP andSQEiCP on both synthetic datasets and Matrix Market NEP Repository arereported. BDCA demonstrated dramatic acceleration to the convergence of DCA toget better numerical solutions, and outperformed KNITRO, FILTERED, and FMINCONsolvers in terms of the average CPU time and average solution precision,especially for large-scale cases.

An Accelerated DC Programming Approach with Exact Line Search for The Symmetric Eigenvalue Complementarity Problem