Research on CMOPSO Particle Swarm Optimization Algorithm for Green Manufacturing Energy System in Ecological Park

In view of the multi-objective optimization to solve the problem of the smallest energy consumption and emissions to the environment for the green manufacturing system, because classical PSO has the characteristics of precocity and cannot ensure to obtain uniform convergence to the optimal solution, combined multi-Objective particle swarm optimization (CMOPSO) is proposed, with adaptive inertia weight and dynamic topology. Update strategy and the dynamic topology is given to balance particle global and local search ability, improving the convergence properties. Finally, an ecological park is taken as example to verify the effectiveness of the algorithm, which can provide guidance and help for green manufacturing enterprises to make energy decisions and plans to meet the green manufacturing goals.