Smart Business Networks Design and Business Genetics

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  title =        "Smart Business Networks Design and Business Genetics",
  author =       "L-F. Pau",
  year =         "2006",
  month =        jun # "~28",
  institution =  "RSM Erasmus University, Erasmus Research Institute of
                 Management (ERIM)",
  type =         "ERIM Report Series",
  number =       "ERS-2006-002-LIS",
  address =      "RSM Erasmus University, Erasmus Research Institute of
                 Management (ERIM), P/O Box 1738, 3000 DR Rotterdam, The
                 Netherlands, email:",
  bibsource =    "OAI-PMH server at",
  format =       "17 pages; 150770 bytes",
  identifier =   "1566-5283",
  language =     "en",
  oai =          "",
  relation =     "ERS; ERS-2006-002-LIS; January 2006; LIS",
  ISSN =         "1566-5283",
  email =        "",
  keywords =     "genetic algorithms, genetic programming, Smart
                 Business Networks, Design of Smart business Network,
                 Genetics, Cellular Automata, Emergence Theory,
                 Computational Geometry, Vorono{\"i}, Smart Business
                 Maps, Business Genetics, Technology Management, HF
                 5001-6182, HE 9713+, HD 69.S8, B6200, M, L63, L96, L14,
                 85.00, 05.42, 05.49, Bedrijfskunde / Bedrijfseconomie,
                 Draadloze Communicatie, GIS, Communicatienetwerken,
                 Computational geometry, Genetische algoritmen, C2.1",
  URL =          "",
  URL =          "",
  abstract =     "With the emergence of smart business networks, agile
                 networks, etc. as important research areas in
                 management, for all the attractiveness of these
                 concepts, a major issue remains around their design and
                 the selection rules. While smart business networks
                 should provide advantages due to the quick connect of
                 business partners for selected functions in a process
                 common to several parties, literature does not provide
                 constructive methods whereby the selection of temporary
                 partners and functions can be done. Most discussions
                 only rely solely on human judgment. This paper
                 introduces both computational geometry, and genetic
                 programming, as systematic methods whereby to display
                 possible partnerships, and also whereby to plan for
                 their effect on the organizations or functions of those
                 involved. The two techniques are also been put in the
                 context of emergence theory. Business maps address the
                 first challenge with the use of Vorono{\"i} diagrams.
                 Cellular automata, with genetic algorithms mimicking
                 living bodies, address the second challenge. This paper
                 does not include experimental results, which have been
                 derived in the high tech area to determine especially
                 the adequateness of systems integrators to set up joint
                 ventures with smaller technology suppliers.",

Genetic Programming entries for Louis-Francois Pau