Konstantinos Boulas
Alexandros Tzanetos
ABSTRACT
Estimating the performance of a production line is a difficult problem because of the enormous number of states that exist when analyzing 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.
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Index Terms
- Acquisition of approximate throughput formulas for serial production lines with parallel machines using intelligent techniques
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