Acquisition of approximate throughput formulas for serial production lines with parallel machines using intelligent techniques

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{boulas_acquisition_2018,

• address = "Rio Patras, Greece",
• title = "Acquisition of approximate throughput formulas for serial production lines with parallel machines using intelligent techniques",
• isbn13 = "978-1-4503-6433-1",
• URL = "http://dl.acm.org/citation.cfm?doid=3200947.3201028",
• DOI = "doi:10.1145/3200947.3201028",
• abstract = "Estimating the performance of a production line is a difficult problem because of the enormous number of states that exist when analysing such systems. In addition to the methods developed to address the problem, it is very useful to have a formula linking the characteristics of the line to its performance. Three cases of sort serial production lines with parallel and identical machines in each workstation are examined in this paper. By using a combinational method that applies genetic programming (GP) and an innovative nature inspired method, named sonar inspired optimization (SIO) to improve the results, three models are derived to obtain the throughput of the corresponding lines. Further work will take place because results derived in this paper are encouraging.",
• language = "en",
• booktitle = "Proceedings of the 10th {Hellenic} {Conference} on {Artificial} {Intelligence}",
• publisher = "ACM Press",
• author = "Konstantinos Boulas and Alexandros Tzanetos and Georgios Dounias",
• month = jul,
• year = "2018",
• note = "Article No 18",
• keywords = "genetic algorithms, genetic programming, parallel-machine stations, performance evaluation, serial production lines, Sonar Inspired Optimization",
• pages = "18:1--18:7",

}

Genetic Programming entries for Konstantinos Boulas Alexandros Tzanetos Georgios Dounias

Citations