Evolutionary computing in manufacturing industry: an overview of recent applications

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

@Article{Oduguwa:2005:ASC,
  author =       "V. Oduguwa and A. Tiwari and R. Roy",
  title =        "Evolutionary computing in manufacturing industry: an
                 overview of recent applications",
  journal =      "Applied Soft Computing",
  year =         "2005",
  volume =       "5",
  pages =        "281--299",
  number =       "3",
  abstract =     "Traditional methods often employed to solve complex
                 real world problems tend to inhibit elaborate
                 exploration of the search space. They can be expensive
                 and often results in sub-optimal solutions.
                 Evolutionary computation (EC) is generating
                 considerable interest for solving real world
                 engineering problems. They are proving robust in
                 delivering global optimal solutions and helping to
                 resolve limitations encountered in traditional methods.
                 EC harnesses the power of natural selection to turn
                 computers into optimisation tools. The core
                 methodologies of EC are genetic algorithms (GA),
                 evolutionary programming (EP), evolution strategies
                 (ES) and genetic programming (GP). This paper attempts
                 to bridge the gap between theory and practice by
                 exploring characteristics of real world problems and by
                 surveying recent EC applications for solving real world
                 problems in the manufacturing industry. The survey
                 outlines the current status and trends of EC
                 applications in manufacturing industry. For each
                 application domain, the paper describes the general
                 domain problem, common issues, current trends, and the
                 improvements generated by adopting the GA strategy. The
                 paper concludes with an outline of inhibitors to
                 industrial applications of optimisation algorithms.",
  owner =        "wlangdon",
  URL =          "http://www.sciencedirect.com/science/article/B6W86-4DJ471C-1/2/1523fa6d00548a23d3f0ea2bce5098a0",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1016/j.asoc.2004.08.003",
}

Genetic Programming entries for Victor Oduguwa Ashutosh Tiwari Rajkumar Roy

Citations