Modelling Genetic Algorithms: From Markov Chains to Dependence with Complete Connections
نویسنده
چکیده
A Timing Analysis of Convergence to Fitness Sharing Equilibrium p. 23 Where Elitists Start Limping: Evolution Strategies at Ridge Functions p. 34 A Bit-Wise Epistasis Measure for Binary Search Spaces p. 47 Inside GA Dynamics: Ground Basis for Comparison p. 57 The Effect of Spin-Flip Symmetry on the Performance of the Simple GA p. 67 Fitness Distance Correlation and Ridge Functions p. 77 Accelerating the Convergence of Evolutionary Algorithms by Fitness Landscape Approximation p. 87
منابع مشابه
Evaluation of First and Second Markov Chains Sensitivity and Specificity as Statistical Approach for Prediction of Sequences of Genes in Virus Double Strand DNA Genomes
Growing amount of information on biological sequences has made application of statistical approaches necessary for modeling and estimation of their functions. In this paper, sensitivity and specificity of the first and second Markov chains for prediction of genes was evaluated using the complete double stranded DNA virus. There were two approaches for prediction of each Markov Model parameter,...
متن کاملTheoretical Analysis of Mutation-Adaptive Evolutionary Algorithms
Adaptive evolutionary algorithms require a more sophisticated modeling than their static-parameter counterparts. Taking into account the current population is not enough when implementing parameter-adaptation rules based on success rates (evolution strategies) or on premature convergence (genetic algorithms). Instead of Markov chains, we use random systems with complete connections - accounting...
متن کاملCopulas for Markovian Dependence
Copulas have been popular to model dependence for multivariate distributions, but have not been used much in modelling temporal dependence of univariate time series. This paper shows some difficulties with using copulas even for Markov processes: some tractable copulas such as mixtures between copulas of complete coand countermonotonicity and independence (Fréchet copulas) are shown to imply qu...
متن کاملStochastic Dynamic Programming with Markov Chains for Optimal Sustainable Control of the Forest Sector with Continuous Cover Forestry
We present a stochastic dynamic programming approach with Markov chains for optimal control of the forest sector. The forest is managed via continuous cover forestry and the complete system is sustainable. Forest industry production, logistic solutions and harvest levels are optimized based on the sequentially revealed states of the markets. Adaptive full system optimization is necessary for co...
متن کاملCyclic Markov chains with an application to an intermediate ENSO model
We develop the theory of cyclic Markov chains and apply it to the El Niño-Southern Oscillation (ENSO) predictability problem. At the core of Markov chain modelling is a partition of the state space such that the transition rates between different state space cells can be computed and used most efficiently. We apply a partition technique, which divides the state space into multidimensional cells...
متن کامل