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Code and Data Repository for A Heuristic for Complementarity Problems Using Difference of Convex Functions
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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.
Institute for Operations Research and the Management Sciences (INFORMS)
Title: Code and Data Repository for A Heuristic for Complementarity Problems Using Difference of Convex Functions
Description:
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.
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