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The Everyday Engineering of Organizational and Engineering Innovation

  • David E. Goldberg

Abstract

This paper discusses how the routine study of the theory and design of genetic algorithms (GAs) has led to a number of unexpected results. Specifically, the paper considers how GA theory and design has led to (1) the design of genetic algorithms that solve hard problems quickly, reliably, and accurately, (2) a system for collaborative innovation, (3) methods for designing organizations more effectively, (4) GAs based on effective clustering in organizations, and (5) an extensible family of facetwise organizational models.

Keywords

Genetic Algorithm Team Size Sweet Spot Design Structure Matrix Innovation Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • David E. Goldberg
    • 1
  1. 1.Department of General EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaIllinois

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