Research On Multi-population Co-evolutionary Multi-objective Particle Swarm Optimization And Its Application

In this thesis, multi-objective particle swarm optimization algorithm based on multi-population co-evolutionary mechanism and its application on economic environmental load dispatch problem in power systems is researched.There are many real-world optimization problems involving multiple objectives that should be optimized simultaneously in industrial production. Particle Swarm Optimization (PSO) has been widely applied to multi-objective optimization due to its fast convergence and ease of implementation. Aiming to solve the problems of the selection of leaders、the retaining of non-dominated solutions and the maintaining of the diversity in the swarm when apply PSO to solve multi-objective problems, the Multi-population Co-evolutionary Multi-objective Particle Swarm Optimization (MPCMOPSO) algorithm is proposed.The swarm is divided into several same size sub-swarms according to the number of objectives, and an external shared archive is used to store the non-dominated solutions and realize the information sharing between every sub-swarm. The velocity update equation is modified correspondingly and the leader is selected based on the density of Pareto solutions. In order to maintain the convergence speed and bring in diversity to the swarms simultaneously, an improved Tent equation based local search strategy is applied to particles in the external archive. An improved adaptive gird strategy is used for maintaining the capacity of the external archive, thus the distribution of non-dominated solutions in the objective space is expanded. Also, the proposed algorithm is comprehensively tested on ZDT benchmark problems with different characteristics and the results are compared with some state-of-the-art multi-objective optimization algorithms. The result shows that MPCMOPSO has superior performance in solving ZDT benchmark problems.Then apply the proposed algorithm to solve economic environmental load dispatch problem in power systems. The valve-point effect and the transmission loss of power systems are considered when building the objective functions of this problem. The proposed algorithm needs to be justified accordingly as there are equality constrains in the problem. Then the proposed algorithm is carried out on the IEEE 30 bus test system with 6 generators. The comparison results show that MPCMOPSO has obtained better load dispatch scheme than other state-of-the-art multi-objective optimization algorithms.