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The problem is considered of optimizing discrete parameters in the presenceof constraints. We use the stochastic sigmoid with temperature and put forwardthe new adaptive gradient method CONGA. The search for an optimal solution iscarried out by a population of individuals. Each of them varies according togradients of the 'environment' and is characterized by two temperatureparameters with different annealing schedules. Unadapted individuals die, andoptimal ones interbreed, the result is directed evolutionary dynamics. Theproposed method is illustrated using the well-known combinatorial problem foroptimal packing of a backpack (0-1 KP).

Optimization of Discrete Parameters Using the Adaptive Gradient Method and Directed Evolution