On the resolution of monotone complementarity problems
Computational Optimization and Applications
Modified Projection-Type Methods for Monotone Variational Inequalities
SIAM Journal on Control and Optimization
Some Noninterior Continuation Methods for LinearComplementarity Problems
SIAM Journal on Matrix Analysis and Applications
A semismooth equation approach to the solution of nonlinear complementarity problems
Mathematical Programming: Series A and B
Mathematics of Operations Research
Neural Networks for Optimization and Signal Processing
Neural Networks for Optimization and Signal Processing
A New Merit Function For Nonlinear Complementarity Problems And A Related Algorithm
SIAM Journal on Optimization
A high-performance neural network for solving linear and quadratic programming problems
IEEE Transactions on Neural Networks
A new neural network for solving linear and quadratic programming problems
IEEE Transactions on Neural Networks
Linear and quadratic programming neural network analysis
IEEE Transactions on Neural Networks
Solving linear programming problems with neural networks: a comparative study
IEEE Transactions on Neural Networks
Stability Analysis of Gradient-Based Neural Networks for Optimization Problems
Journal of Global Optimization
Journal of Global Optimization
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An artificial neural network is proposed in this paper for solving the linear complementarity problem. The new neural network is based on a reformulation of the linear complementarity problem into the unconstrained minimization problem. Our new neural network can be easily implemented on a circuit. On the theoretical aspect, we analyze the existence of the equilibrium points for our neural network. In addition, we prove that if the equilibrium point exists for the neural network, then any such equilibrium point is both asymptotically and bounded (Lagrange) stable for any initial state. Furthermore, linear programming and certain quadratical programming problems (not necessarily convex) can be also solved by the neural network. Simulation results on several problems including a nonconvex one are also reported.