An Altered Adaptive Genetic Algorithm for Solving Energy Consumption Problems

An altered1 adaptive genetic algorithm (AAGA) with crossover strategy and mutation strategy is proposed in this paper, in order to solve the problems of simple genetic algorithm (SGA) and adaptive genetic algorithm (AGA).The problems include the phenomenon of premature convergence and the trouble of local optimum. The proposed AAGA method compared with SGA and AGA by investigation and research on the production process of a tire manufacturer. The analysis results indicate that the average energy consumption and minimum value of AAGA is lower than that of the other two algorithms, and the convergence performance of the proposed algorithm is better. The new method can provide a more effective technical guidance to solve the problems of energy optimization in practical application.