Abstract
An improved algorithm—multi-objective particle swarm optimization with swarm energy conservation (SEC-MOPSO) is proposed, which is aimed to solve the problem of convergence and distribution in multi-objective particle swarm optimization (MOPSO) algorithm. Swarm energy conservation mechanism is used to update the velocity and position of particles. Besides, non-dominated sorting method, adaptive grid mechanism and elitism mechanism are also incorporated into SEC-MOPSO algorithm to improve searching capabilities and avoid falling into the second-best non-dominated front. The simulation results show that SEC-MOPSO has better performance than MOPSO in distribution and convergence.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
