Pages that link to "Item:Q1354022"

The following pages link to Modeling genetic algorithms with Markov chains. (Q1354022):

Displaying 50 items.

• Monotonicity of fitness landscapes and mutation rate control (Q338348) (← links)
• An agent-based model of hierarchic genetic search (Q356405) (← links)
• A Markov chain that models genetic algorithms in noisy environments (Q419865) (← links)
• Finding all minimal elements of a finite partially ordered set by genetic algorithm with a prescribed probability (Q428481) (← links)
• Markov chain analysis of self-organizing mobile nodes self-organizing mobile nodes (Q444793) (← links)
• Theoretical analysis of steady state genetic algorithms (Q489236) (← links)
• Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms (Q543817) (← links)
• Practical performance models of algorithms in evolutionary program induction and other domains (Q622115) (← links)
• A unified framework for population-based metaheuristics (Q646652) (← links)
• Markov modelling and parameterisation of genetic evolutionary test generations (Q656959) (← links)
• The dynamics of a genetic algorithm for simple random Ising systems (Q678365) (← links)
• Markov model of sex-linked recessive trait transmission (Q699413) (← links)
• A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues (Q726210) (← links)
• Towards an analytic framework for analysing the computation time of evolutionary algorithms (Q814443) (← links)
• A comparative runtime analysis of heuristic algorithms for satisfiability problems (Q835804) (← links)
• A general steady state distribution based stopping criteria for finite length genetic algorithms (Q853021) (← links)
• The effect of multiple optima on the simple GA run-time complexity (Q857359) (← links)
• A genetic system based on simulated crossover of sequences of two-bit genes (Q857396) (← links)
• On initial populations of a genetic algorithm for continuous optimization problems (Q878224) (← links)
• A new genetic algorithm for solving nonconvex nonlinear programming problems (Q924398) (← links)
• Linear analysis of genetic algorithms (Q1276251) (← links)
• A Markov chain analysis of genetic algorithms with power of 2 cardinality alphabets (Q1278478) (← links)
• A branching process model for genetic algorithms (Q1352099) (← links)
• Optimizing epochal evolutionary search: population-size independent theory. (Q1574373) (← links)
• Random heuristic search: applications to GAs and functions of unitation. (Q1574374) (← links)
• A discipline of evolutionary programming (Q1575454) (← links)
• Genetic algorithms, pseudo-random numbers generators, and Markov chain Monte Carlo methods (Q1605867) (← links)
• On the convergence of biogeography-based optimization for binary problems (Q1717756) (← links)
• Sorting by swaps with noisy comparisons (Q1725654) (← links)
• Designing polymer blends using neural networks, genetic algorithms, and Markov chains (Q1768489) (← links)
• Population aggregation based on fitness (Q1768778) (← links)
• Application of Markov chains to linked genes with interference. II: Genotypic selection (Q1802905) (← links)
• Global optimization with exploration/selection algorithms and simulated annealing (Q1872426) (← links)
• Theory of genetic algorithms. II: Models for genetic operators over the string-tensor representation of populations and convergence to global optima for arbitrary fitness function under scaling (Q1884972) (← links)
• Metaheuristics: A bibliography (Q1919858) (← links)
• The algebra of genetic algorithms (Q1924788) (← links)
• A proof of the Vose-Liepins conjecture (Q1924790) (← links)
• A closer look at mutation in genetic algorithms (Q1924791) (← links)
• A mathematical analysis of the long-run behavior of genetic algorithms for social modeling (Q1933789) (← links)
• A Markov model of polygenic inheritance (Q2088545) (← links)
• A self-adaptive migration model genetic algorithm for data mining applications (Q2385684) (← links)
• A new approach to estimating the expected first hitting time of evolutionary algorithms (Q2389686) (← links)
• Learning genetic algorithm parameters using hidden Markov models (Q2433443) (← links)
• Backward-chaining evolutionary algorithms (Q2457607) (← links)
• Phase transitions and symmetry breaking in genetic algorithms with crossover (Q2503278) (← links)
• Some results about the Markov chains associated to GPs and general EAs (Q2503342) (← links)
• Theoretical advances in artificial immune systems (Q2518373) (← links)
• The unified method analyzing convergence of genetic algorithms (Q2745617) (← links)
• Continuous dynamical system models of steady-state genetic algorithms (Q2776415) (← links)
• Multistage non homogeneous Markov chain modeling of the non homogeneous genetic algorithm and convergence results (Q2807805) (← links)