A Genetic Programming Heuristic for the One-Machine Total Tardiness Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Christos Dimopoulos and Ali M. S. Zalzala",
  title =        "A Genetic Programming Heuristic for the One-Machine
                 Total Tardiness Problem",
  booktitle =    "Proceedings of the Congress on Evolutionary
  year =         "1999",
  editor =       "Peter J. Angeline and Zbyszek Michalewicz and 
                 Marc Schoenauer and Xin Yao and Ali Zalzala",
  volume =       "3",
  pages =        "2207--2214",
  address =      "Mayflower Hotel, Washington D.C., USA",
  publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ
                 08855-1331, USA",
  month =        "6-9 " # jul,
  organisation = "Congress on Evolutionary Computation, IEEE / Neural
                 Networks Council, Evolutionary Programming Society,
                 Galesia, IEE",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, manufacturing
                 optimization, benchmark problems, dispatching rules,
                 due date tardiness, due date tightness, genetic
                 programming heuristic, local search techniques,
                 manufacturing optimisation problems, modified genetic
                 programming framework, one-machine total tardiness
                 problem, permutations, dispatching, evolutionary
                 computation, heuristic programming, optimisation,
                 scheduling, search problems",
  ISBN =         "0-7803-5536-9 (softbound)",
  ISBN =         "0-7803-5537-7 (Microfiche)",
  DOI =          "doi:10.1109/CEC.1999.785549",
  abstract =     "Genetic programming has rarely been applied to
                 manufacturing optimisation problems. In this report we
                 investigate the potential use of genetic programming
                 for the solution of the one-machine total tardiness
                 problem. Combinations of dispatching rules are employed
                 as an indirect way of representing permutations within
                 a modified genetic programming framework. Hybridisation
                 of genetic programming with local search techniques is
                 also introduced, in an attempt to improve the quality
                 of solutions. All the algorithms are tested on a large
                 number of benchmark problems with different levels of
                 tardiness and tightness of due dates",
  notes =        "CEC-99 - A joint meeting of the IEEE, Evolutionary
                 Programming Society, Galesia, and the IEE.

                 Library of Congress Number = 99-61143",

Genetic Programming entries for Christos Dimopoulos Ali M S Zalzala