Neural Networks for Solving Quadratic Assignment Problems
نویسنده
چکیده
Abstract— In this paper the Hopfield neural networks are adopted to solve the quadratic assignment problem, which is a generalization of the traveling salesman’s problem (TSP), the graph-partitioning problem (GPP), and the matching problem. When the Hopfield neural network was applied alone, a sub-optimal solution was obtained. By adding the 2exchange we obtained a solution very close to the optimum solution. The relationship between the gain of neuron λ and the penalty coefficient α of the Hopfield model has been experimentally analyzed.
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