A Multivalued Recurrent Neural Network for the Quadratic Assignment Problem

Abstract : The Quadratic Assignment Problem (QAP) is an NP-complete problem. Different algorithms have been proposed using different methods. In this paper, the problem is formulated as a minimizing problem of a quadratic function with restrictions incorporated to the computational dynamics and variables Si ∈{1,2,..., n}. To solve this problem a recurrent neural network multivalued (RNNM) is proposed. We present four computational dynamics and we demonstrate that the energy of the neuron network decreases or remains constant according to the Computer Dynamic defined.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-364 (Part II), pp.132-140, 2011, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-23960-1_17〉
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Gracián Triviño, José Muñoz, Enrique Domínguez. A Multivalued Recurrent Neural Network for the Quadratic Assignment Problem. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-364 (Part II), pp.132-140, 2011, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-23960-1_17〉. 〈hal-01571459〉

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