TY - GEN
T1 - Sequential metamodelling with genetic programming and particle swarms
AU - Can, Birkan
AU - Heavey, Cathal
PY - 2009
Y1 - 2009
N2 - This article presents an application of two main component methodologies of evolutionary algorithms in simulation-based metamodelling. We present an evolutionary framework for constructing analytical metamodels and apply it to simulations of manufacturing lines with buffer allocation problem. In this framework, a particle swarm algorithm is integrated to genetic programming to perform symbolic regression of the problem. The sampling data is sequentially generated by the particle swarm algorithm, while genetic programming evolves symbolic functions of the domain. The results are promising in terms of efficiency in design of experiments and accuracy in global metamodelling.
AB - This article presents an application of two main component methodologies of evolutionary algorithms in simulation-based metamodelling. We present an evolutionary framework for constructing analytical metamodels and apply it to simulations of manufacturing lines with buffer allocation problem. In this framework, a particle swarm algorithm is integrated to genetic programming to perform symbolic regression of the problem. The sampling data is sequentially generated by the particle swarm algorithm, while genetic programming evolves symbolic functions of the domain. The results are promising in terms of efficiency in design of experiments and accuracy in global metamodelling.
UR - http://www.scopus.com/inward/record.url?scp=77951644647&partnerID=8YFLogxK
U2 - 10.1109/WSC.2009.5429276
DO - 10.1109/WSC.2009.5429276
M3 - Conference contribution
AN - SCOPUS:77951644647
SN - 9781424457700
T3 - Proceedings - Winter Simulation Conference
SP - 3150
EP - 3157
BT - Proceedings of the 2009 Winter Simulation Conference, WSC 2009
T2 - 2009 Winter Simulation Conference, WSC 2009
Y2 - 13 December 2009 through 16 December 2009
ER -