Title :
Convergence of evolutionary algorithms on the n-dimensional continuous space
Author :
Agapie, Alexandru ; Agapie, Mircea ; Rudolph, Gunter ; Zbaganu, Gheorghita
Author_Institution :
Appl. Math. Dept., Bucharest Univ. of Econ. Studies, Bucharest, Romania
Abstract :
Evolutionary algorithms (EAs) are random optimization methods inspired by genetics and natural selection, resembling simulated annealing. We develop a method that can be used to find a meaningful tradeoff between the difficulty of the analysis and the algorithms´ efficiency. Since the case of a discrete search space has been studied extensively, we develop a new stochastic model for the continuous n-dimensional case. Our model uses renewal processes to find global convergence conditions. A second goal of the paper is the analytical estimation of the computation time of EA with uniform mutation inside the (hyper)-sphere of volume 1, minimizing a quadratic function.
Keywords :
evolutionary computation; random processes; simulated annealing; stochastic processes; discrete search space; evolutionary algorithm; global convergence condition; n-dimensional continuous space; quadratic function; random optimization method; renewal process; simulated annealing; stochastic model; uniform mutation; Computational complexity; evolutionary computation; optimization; stochastic processes; Algorithms; Biomimetics; Computer Simulation; Evolution, Molecular; Models, Genetic; Models, Statistical; Stochastic Processes;
Journal_Title :
Cybernetics, IEEE Transactions on
DOI :
10.1109/TCYB.2013.2257748