A self-adaptive migration model genetic algorithm for data mining applications
Information Sciences: an International Journal
Genetic local search for multicast routing with pre-processing by logarithmic simulated annealing
Computers and Operations Research
Information Sciences: an International Journal
Analog circuit optimization system based on hybrid evolutionary algorithms
Integration, the VLSI Journal
Computers and Operations Research
Information Sciences: an International Journal
On the analysis of the simple genetic algorithm
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Finite Markov Chain Results in Evolutionary Computation: A Tour d'Horizon
Fundamenta Informaticae
ε - Optimal Stopping Time for Genetic Algorithms
Fundamenta Informaticae
Analyzing stability of algorithmic systems using algebraic constructs
ICT-EurAsia'13 Proceedings of the 2013 international conference on Information and Communication Technology
A novel adaptive fuzzy predictive control for hybrid systems with mixed inputs
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
Chaotic Evolution: fusion of chaotic ergodicity and evolutionary iteration for optimization
Natural Computing: an international journal
Variance as a Stopping Criterion for Genetic Algorithms with Elitist Model
Fundamenta Informaticae
A computational intelligence optimization algorithm: Cloud drops algorithm
Integrated Computer-Aided Engineering
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This paper analyzes the convergence properties of the canonical genetic algorithm (CGA) with mutation, crossover and proportional reproduction applied to static optimization problems. It is proved by means of homogeneous finite Markov chain analysis that a CGA will never converge to the global optimum regardless of the initialization, crossover, operator and objective function. But variants of CGA's that always maintain the best solution in the population, either before or after selection, are shown to converge to the global optimum due to the irreducibility property of the underlying original nonconvergent CGA. These results are discussed with respect to the schema theorem