Team Progress Algorithm for Global Optimization of Multimodal Problems
BO Ya-ming · Journal of Nanjing University of Posts and Telecommunications · 2008
A novel two-group evolution algorithm,which is called team progress algorithm (TPA),is presented in this paper by simulating the member actions of learning,exploring and the member renewal rules of a team.In the algorithm,the team members are divided into the elite and plain groups with their respective epitomes,the manipulations of learning and exploration are properly defined,and the member renewal rules are reasonably established.The members’ division of action can emerge during the search procedure,which makes the algorithm possesses the potential of global,local and directional search.Numerical results verify that the new algorithm has the properties of simple implementation,high success rate for global optimization,fast convergence,low computation cost,strong robustness and easy determination of the parameters,and that it is valuable for different optimization applications.