The optimization of beer recipe based on an improved ant colony optimization

The beer recipe optimization is a effective way for reducing the brewing enterprises. Because the recipe optimization belongs to NP-hard problem, It is difficult to obtain the global optimal solution for the traditional optimization algorithm. Though ant colony optimization (ACO) is suitable for solving the combinatorial optimization problems, it still has weakness in solving continuous optimization problems. Therefore, a new ant colony optimization was presented in this paper, and the whole solution space was adjusted properly by using dynamic mining in iterative process. After that, the optimization of beer recipe based on the improved ACO was studied, to reduce the cost of raw materials under the condition of the production constraints. And Simulation results had been showed that comparing with other algorithms, the improved algorithm has better global optimization ability and robustness.