Optimization application of an improved genetic algorithm in coal mine distribution network planning

In view of problems of premature convergence of application of traditional genetic algorithm in distribution network planning in mining area to affect accuracy of planning, a multi-population simulated annealing and genetic algorithm was proposed. The algorithm takes the minimum year planning cost as objective function , and combines with advantage of simulated annealing algorithm, adds multi-population characteristics at the same time, so as to solve the problem of premature convergence in power distribution network planning and improve search efficiency and convenient to obtain the global optimal solution in the planning. The experimental results show that cost planning, iteration times are significantly reduced by use of multi-population simulated annealing and genetic algorithm to optimize mine distribution network, the running time is reduced by about six percent, the error rate is reduced by about three percent compared with the original algorithm, and the algorithm is more effective and efficient.