Approximating Throughput of Small Production Lines Using Genetic Programming

Konstantinos Boulas (), Georgios Dounias () and Chrissoleon Papadopoulos ()
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Konstantinos Boulas: University of the Aegean
Georgios Dounias: University of the Aegean
Chrissoleon Papadopoulos: Aristotle University of Thessaloniki

A chapter in Operational Research in Business and Economics, 2017, pp 185-204 from Springer

Abstract: 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 encouraging.

Keywords: Production lines; Genetic programming; Symbolic regression; Throughput (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-319-33003-7_9

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DOI: 10.1007/978-3-319-33003-7_9

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