Site selection optimization method based on multi-modal multi-objective particle swarm optimization algorithm

The invention discloses a site selection optimization method based on a multi-modal multi-objective particle swarm optimization algorithm. The method comprises the steps of employing multiple populations based on a Kmeans clustering method to locate more equivalent Pareto optimal solution sets in a decision space, and employing a grid mechanism to explore a high-quality solution in the decision space. Two operations are added in the environment selection operation, including removing a low-efficiency solution and updating a non-dominated solution archive, so that the diversity of the solutionis maintained, the solution is close to a real non-dominated solution, and the convergence of the solution in a target space is maintained. The method is advantaged in that more equivalent Pareto optimal solution sets can be found in the decision space, meanwhile, a good balance is kept between the diversity of the Pareto optimal solution sets in the decision space and the convergence of the Pareto optimal solution sets i