Dual Hopfield Methods for Large-Scale Mixed-Integer Programming
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC)(2018)
摘要
We present a novel heuristic first order method for large-scale mixed-integer programs, more specifically we focus on mixed-integer quadratically constrained quadratic programs. Our method builds on Lagrangian relaxation techniques and Hopfield Neural Networks. For illustration, we apply this method to an economic load dispatch problem and compare with two convex approximation techniques.
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关键词
mixed-integer quadratically constrained quadratic programs,Hopfield Neural Networks,convex approximation techniques,economic load dispatch problem,large-scale mixed-integer programs,heuristic first order method,large-scale mixed-integer programming,dual Hopfield methods
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