Approximating Throughput of Small Production Lines Using Genetic Programming

  • Konstantinos Boulas
  • Georgios DouniasEmail author
  • Chrissoleon Papadopoulos
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)


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 encouraging.


Production lines Genetic programming Symbolic regression Throughput 



This research has been co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program: Thales (ASPASIA). Investing in knowledge society through the European Social Fund.


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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Konstantinos Boulas
    • 1
  • Georgios Dounias
    • 1
    Email author
  • Chrissoleon Papadopoulos
    • 2
  1. 1.Management and Decision Engineering Laboratory (MDE-Lab), Department of Financial and Management Engineering, Business SchoolUniversity of the AegeanChiosGreece
  2. 2.Department of EconomicsAristotle University of ThessalonikiThessalonikiGreece

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