Computable rate of convergence in evolutionary computation
Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997) - Tập 1 - Trang 88-93 vol.1
Tóm tắt
The broad field of evolutionary computation (EC)-including genetic algorithms as a special case-has attracted much attention in the last several decades. Many bold claims have been made about the effectiveness of various EC algorithms. These claims have centered on the efficiency, robustness, and ease of implementation of EC approaches. Unfortunately, there seems to be little theory to support such claims. One key step to formally evaluating or substantiating such claims is to establish rigorous results on the rate of convergence of EC algorithms. This paper presents a computable rate of convergence for a class of ECs that includes the standard genetic algorithm as a special case.
Từ khóa
#Convergence #Evolutionary computation #Genetic algorithms #Genetic mutations #Laboratories #Physics computing #Robustness #Stochastic processes #Monte Carlo methods #Computational modelingTài liệu tham khảo
10.1162/evco.1996.4.4.395
10.1109/21.370197
vose, 1991, Punctuated equilibria in genetic search, Complex Systems, 5, 31
schwefel, 1995, Evolution and Optimum Seeking
10.1109/ACC.2000.879533
rudolph, 1997, Convergence rates of evolutionary algorithms for a class of convex objective functions, Control and Cybernetics, 26, 375
rudolph, 1998, Finite markov chain results in evolutionary computation: A tour d'horizon, Fundamenta Informaticae, 34, 1
10.1109/ICEC.1996.542332
rudolph, 1997, Convergence Properties of Evolutionary Algorithms
10.1162/evco.1993.1.3.269
vose, 1999, The Simple Genetic Algorithm
davis, 1991, Toward an Extrapolation of the Simulated Annealing Convergence Theory on to the Simple Genetic Algorithm
10.1162/evco.1995.3.1.81
rudolph, 1994, Convergence analysis of canonical genetic algorithms, IEEE Transactions on Neural Networks, 5, 96, 10.1109/72.265964
10.1109/4235.910461
iosifescu, 1980, Finite Markov Processes and Their Applications
holland, 1975, Adaptation in Natural and Artificial Systems
eiben, 1991, Global convergence of genetic algorithms: A markov chain analysis, Parallel Problem Solving from Nature, 4
qi, 1994, Theoretical analysis of evolutionary algorithms with infinite population size in continuous space, part i: Basic properties, IEEE Transactions on Neural Networks, 5, 102, 10.1109/72.265965
10.1007/BF01530781
