The design of innovation: Lessons from genetic algorithms, lessons for thereal world

This article considers some of the connections between genetic algorithms ( GAs)-search procedures based on the mechanics of natural selection and natu ral genetics-and human innovation. Simply stated, innovation has been a sou rce of inspiration for thinking about genetic algorithms, and as the algori thms have improved. GAs have become increasingly interesting computational models of the processes of innovation. The article reviews the basics of ge netic algorithm operation and connects the basic mechanics to two processes of innovation: continual improvement and discontinuous change. Thereafter, some of the technical lessons of genetic algorithm processing are reviewed and their implications are briefly explored in the context of organization al change. (C) 2000 Elsevier Science Inc.