Approximating Throughput of Small Production Lines Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Konstantinos Boulas and Georgios Dounias and 
                 Chrissoleon Papadopoulos",
  title =        "Approximating {Throughput} of {Small} {Production}
                 {Lines} {Using} {Genetic} {Programming}",
  booktitle =    "Operational {Research} in {Business} and {Economics}:
                 4th {International} {Symposium} and 26th {National}
                 {Conference} on {Operational} {Research}, 2015",
  editor =       "Evangelos Grigoroudis and Michael Doumpos",
  year =         "2017",
  pages =        "185--204",
  address =      "Chania, Greece",
  month =        "4–6 " # jun,
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, production
                 lines, symbolic regression, throughput",
  isbn13 =       "978-3-319-33003-7",
  URL =          "",
  DOI =          "doi:10.1007/978-3-319-33003-7_9",
  abstract =     "Genetic Programming (GP) has been used in a variety of
                 fields to solve complicated problems. This paper shows
                 that GP can be applied in the domain of serial
                 production systems for acquiring useful measurements
                 and line characteristics such as throughput. Extensive
                 experimentation has been performed in order to set up
                 the genetic programming implementation and to deal with
                 problems like code bloat or over fitting. We improve
                 previous work on estimation of throughput for three
                 stages and present a formula for the estimation of
                 throughput of production lines with four stations.
                 Further work is needed, but so far, results are

Genetic Programming entries for Konstantinos Boulas Georgios Dounias Chrissoleon T Papadopoulos