Design of dynamic resource regulation algorithm by integrating improved Genetic Algorithm
In order to reduce the purchase and maintenance costs of Smart grid hardware equipment and improve the utilization efficiency of various resources,this paper proposes a dynamic resource regulation algorithm based on the combination of improved Genetic Algorithm(GA)and Ant Colony Optimization(ACO),and constructs a corresponding model.By introducing a time load dual fitness function into the traditional GA,the accuracy of the global optimal solution of the GA has been improved.In the traditional ACO,the time cost double function is used to determine the Pheromone,which improves the initial optimization speed of the ACO.The dynamic fusion strategy is used to combine the improved GA and the improved ACO to build the ACO-GA dynamic resource regulation algorithm.The simulation results of the example show that the proposed ACO-GA dynamic resource regulation algorithm has an execution time of 120 ms and an imbalance value of 0.52 when the number of tasks is 400.Compared to other algorithms,the ACO-GA dynamic resource regulation algorithm has the lowest execution time and the most stable imbalance value,proving its feasibility for resource regulation.
万方数据
维普
