Optimal strategies multiproduct food businessoperation using genetic algorithms and particle svarm

In this paper the authors propose an optimization problem of control over the operation of the company, which produces food products with a large range of items delivered in the form of a nonlinear programming problem with a vector criterion, for which we have developed a modified genetic algorithm, and also one of the innovative heuristic methods, particle swarm optimization. The developed software using two algorithms of optimization on the user selection - genetic algorithm or particle swarm optimization algorithm.