ASYMPTOTIC CONVERGENCE PROPERTIES OF GENETIC ALGORITHMS AND EVOLUTIONARY PROGRAMMING: ANALYSIS AND EXPERIMENTS

DOI10.1080/01969729408902335zbMath0811.68082OpenAlexW2026859834MaRDI QIDQ4301868

David B. Fogel

Publication date: 18 August 1994

Published in: Cybernetics and Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01969729408902335

zbMATH Keywords

genetic algorithmsevolutionary programmingcomplex nonlinear optimization problems

Mathematics Subject Classification ID

Game theory (91A99) Parallel algorithms in computer science (68W10)

Related Items (12)

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 ⋮ A single component mutation evolutionary programming ⋮ The multifactor nature of the volatility of futures markets ⋮ A single-point mutation evolutionary programming ⋮ Metaheuristics: A bibliography ⋮ Taboo evolutionary programming: a new method of global optimization ⋮ Generalized evolutionary programming with Lévy-type mutation ⋮ Theory of genetic algorithms ⋮ On the convergence of a population-based global optimization algorithm ⋮ CONTINUOUS EVOLUTIONARY PROGRAMMING: ANALYSIS AND EXPERIMENTS ⋮ Reconstructing the nonlinear dynamical systems by evolutionary computation techniques ⋮ A theoretical analysis on mutation operator of standard genetic algorithm

Cites Work

• Heuristic combinatorial optimization by simulated Darwinian evolution: A polynomial time algorithm for the traveling salesman problem
• A modified genetic algorithm for optimal control problems
• Approximation Theorems of Mathematical Statistics

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