Artificial Glowworm Swarm Optimization Algorithm for Solving Multi-Objective Constrained Optimization

Focused on the disadvantages of some current constrained optimization algorithm, glowworm swarm multi-objective optimization algorithm ( GSMOA） is proposed in this paper. The main character of this algorithm conforms to feasibility rules and adapts self- adaptive penalty function to search feasible solutions. This algorithm has been tested on 4 standard functions and it shows that the proposed algorithm has more advantage in the convergence rate and the solution precision.