Approximating Throughput of Small Production Lines Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InCollection{boulas_approximating_2017,

• 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 = "http://link.springer.com/10.1007/978-3-319-33003-7_9",
• 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 encouraging.",

}

Genetic Programming entries for Konstantinos Boulas Georgios Dounias Chrissoleon T Papadopoulos

Citations