Exponential chaotic tabu search hardware for quadratic assignment problems using switched-current chaotic neuron IC

The quadratic assignment problem (QAP) is one of the nondeterministic polynomial (NP)-hard combinatorial optimization problems. One of the heuristic algorithms for the QAP is the tabu-search. The exponential tabu-search has been implemented on a neural network, and further it has been extended to be driven by chaotic dynamics based on a chaotic neural network for efficient search. Moreover, chaotic dynamics has also been exploited to avoid the local minima problem. We propose a chaos driven tabu-search neural network hardware system with switched-current chaotic neuron ICs. We build a mixed analog/digital system for the size-10 QAP.