Code and Data Repository for A Heuristic for Complementarity Problems Using Difference of Convex Functions
该仓库提供了使用凸函数差方法求解线性和非线性互补问题的启发式算法实现，所有算法用Python编写，适合研究优化问题的学者参考。
The repository contains the implementation of a heuristic for solving linear and nonlinear complementarity problems (LCPs and NCPs) using a difference of convex functions (DC) approach. The method is referred to as DCA-BL (Difference of Convex Function Algorithms for Bilinear Terms). All algorithms are implemented in Python. LCP problem instances are implemented using the Pyomo modeling language, while NCP instances are implemented using gurobipy. The heuristic is based on the DCA framework, which iteratively solves a sequence of convex approximations to the original non-convex problem.