Study On Adaptive Grouping Ant Colony Algorithm And Its Application In Distribution Network Grid Planning

Ant colony algorithm is an efficient meta-heuristic search technology used to solve combinatorial optimization problems.It has strong robustness and excellent distributed computer system.It has been successfully applied in many optimization problems.The basic ant colony algorithm is easy to fall into the local optimal solution and enter the stagnant state in the process of solving the optimization problem.At the same time,it is accompanied by slow convergence speed and other problems.However,grouping the ants in the ant colony algorithm can enhance the global search ability of the algorithm.And can speed up the convergence speed of the algorithm.The existing grouping strategy is mainly to group the ant population into a fixed number of groups,or to group the ants into groups with different divisions of labor.These grouping methods improve the solution performance of the ant colony algorithm to a certain extent,but do not make full use of the ant colony algorithm.There is still room for research and improvement in the global search ability and local search ability in the group grouping strategy.Distribution network grid planning is an important part of distribution network planning,which can bring huge economic and social benefits to the society.The traditional mathematical optimization method is time-consuming and inefficient to solve the problem of distribution network frame planning.Therefore,this paper mainly researches and improves the ant colony algorithm,and applies the improved ant colony algorithm to solve the problem of distribution network planning.The main work completed and the research results obtained in this paper are as follows:(1)Analyze the existing improved ant colony algorithm "parallel ant colony system",focus on the analysis of the parameter selection in the grouping strategy of the parallel ant colony system,and innovatively study the influence of the four newly defined parameters of the grouping strategy on the performance of the algorithm.The test plan is designed by orthogonal experiment design method,and the rank score of the optimal error Friedman test is used as the evaluation index,and the optimal parameter combination of a parallel ant colony system grouping strategy is obtained,which is an improvement of the parallel ant colony system.And lay the foundation for its application in other fields.(2)An adaptive grouping ant colony algorithm is proposed.The algorithm is improved on the basis of parallel ant colony system.According to the analysis of the grouping number of parallel ant colony system grouping strategy,an adaptive grouping algorithm is proposed.Strategy,the number of groups in the early stage of the algorithm makes the algorithm’s global search more robust and expands the range of feasible solutions,and the number of groups in the later stage of the algorithm makes the local search of the algorithm more effective,which improves the convergence speed and solution performance of the ant colony algorithm.(3)According to the characteristics of the distribution network structure,using the spanning tree strategy,the solution scheme of the distribution network planning problem is constructed into a tree structure,and then the adaptive grouping ant colony algorithm proposed in the article is applied to the distribution network In the grid planning,the simulation results show that the improved algorithm proposed in this paper can effectively solve the problem of distribution grid planning,not only produces a better planning scheme,but also optimizes faster and better convergence performance.