Finite Markov chain analysis of genetic algorithms
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Local search, reducibility and approximability of NP-optimization problems
Information Processing Letters
Approximate solution of NP optimization problems
Theoretical Computer Science
New local search approximation techniques for maximum generalized satisfiability problems
Information Processing Letters
Some optimal inapproximability results
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
A tractable Walsh analysis of SAT and its implications for genetic algorithms
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Induction: Processes of Inference, Learning, and Discovery
Induction: Processes of Inference, Learning, and Discovery
Global Convergence of Genetic Algorithms: A Markov Chain Analysis
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
A Genetic Model and the Hopfield Networks
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Modeling simple genetic algorithms
Evolutionary Computation
The equation for response to selection and its use for prediction
Evolutionary Computation
A genetic model based on simulated crossover of quaternary genes for quadratic fitness
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A genetic system based on simulated crossover of sequences of two-bit genes
Theoretical Computer Science
Analysis of a genetic model with finite populations
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
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In this paper, a genetic model based on the operations of recombination and mutation is studied and applied to combinatorial optimization problems. Results are: 1. The equations of the deterministic dynamics in the thermodynamic limit (infinite populations) are derived and, for a sufficiently small mutation rate, the attractors are characterized; 2. A general approximation algorithm for combinatorial optimization problems is designed. The algorithm is applied to the Max Ek-Sat problem, and the quality of the solution is analyzed. It is proved to be optimal for k ≥ 3 with respect to the worst case analysis; for Max E3-Sat the average case performances are experimentally compared with other optimization techniques.