Application of Genetic Programming to Finance and Operations Management

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@PhdThesis{kleinau:thesis,
  author =       "Peer Kleinau",
  title =        "Application of Genetic Programming to Finance and
                 Operations Management",
  school =       "University of Muenster, Germany",
  year =         "2003",
  email =        "peer.kleinau@gmx.de",
  keywords =     "genetic algorithms, genetic programming, inventory
                 control, option pricing, credit risk",
  size =         "pages",
  abstract =     "In this work the application of Genetic Programming to
                 three common problems arising in the context of
                 Business Administration is analysed. Genetic
                 Programming is based on the basic principles of natural
                 evolution. It adapts some common features of Genetic
                 Algorithms, such as selection, crossover, and mutation.
                 In contrast to Genetic Algorithms which use strings of
                 fixed length, Genetic Programming operates on variable
                 tree structures that make the algorithm capable to
                 solve a great variety of problems. Numerous
                 instructions are given how researchers can develop
                 useful applications in Business Administration with
                 Genetic Programming. In the context of option pricing,
                 Genetic Programming can develop formulae that provide
                 better results than the famous Black and Scholes model.
                 In rating experiments, rating classification simulators
                 are found which give meaningful insights into Standard
                 and Poor s rating assignments. In studies related to
                 the topic of inventory control, Genetic Programming
                 finds both optimal inventory control policies for
                 problems with a low complexity and specialised
                 heuristics for complex problems which are comparable or
                 even better than state-of-the-art heuristics.",
  notes =        "published as \cite{kleinau:thesis_book}",
}

Genetic Programming entries for Peer Kleinau

Citations