Chaotic Neural Network With Application In Combinatorial Optimization

This dissertation aims at chaotic artificial neural network for solving combinational optimization problems. Because the artificical neural network that realized easily by electric circuit is high concurrent,more and more people research it.Although the Hopfield network to solve combinatorial optimization problems came to the startling results But there is also much room for research and improvement.In particular,the Hopfield network to solve combinational optimization constraint,meet the constraint conditions and access to high-quality solution is a need to balance contradictory.Network converges to the energy function of local minima, rather than the global optimal solution.Network Optimization largely depends on network parameters that are less robust parameters.Hopfield network itself is a nonlinear dynamical system to solve nonlinear control problems unique advantages,but this side and the rarely studied.To solve the above problem,this paper presents a Hopfield network of corrective measures,and will improve the Hopfield network application in a class assignment: Hopfield network in the non-equilibrium Bassignment and document distribution applications; Based on the Hopfield networkJob Shop Scheduling application.