A Random Function Based Framework for Evolutionary Algorithms.
Larry D. Merkle, Gary B. Lamont · 1997
Evolutionary algorithms (EAs) are stochastic, population-based algorithms inspired by the natural processes of recombination, mutation, and selection. EAs are often employed as optimum seeking techniques. A formal framework for EAs is proposed, in which evolutionary operators are viewed as mappings from parameter spaces to spaces of random functions. Formal de nitions within this framework capture the distinguishing characteristics of the classes of recombination, mutation, and selection operators. A speci c EA, the generalized fast messy genetic algorithm, is de ned within the proposed framework. 1