Optimization with Potts Neural Networks

• The Potts Neural Network approach to non-binary discrete optimizationproblems is described. It applies to problems that can be described asa set of elementary 'multiple choice' options. Instead of the conventionalbinary (Ising) neurons, mean field Potts neurons, having several availablestates, are used to describe the elementary degrees of freedom of suchproblems. The dynamics consists of iterating the mean field equationswith annealing until convergence. Due to its deterministic character, the method is quite fast. Whenapplied to problems of graph partition and scheduling types, itproduces very good solutions also for problems of considerable size.

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NATURVETENSKAP  -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Bioinformatics (hsv//eng)

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