TY - GEN
T1 - On the Performance of Master-Slave Parallelization Methods for Multi-Objective Evolutionary Algorithms
AU - Zavoianu, Ciprian
AU - Lughofer, Edwin
AU - Koppelstätter, Werner
AU - Weidenholzer, Günther
AU - Amrhein, Wolfgang
AU - Klement, Erich
PY - 2013/6
Y1 - 2013/6
N2 - This paper is focused on a comparative analysis of the performance of two master-slave parallelization methods, the basic generational scheme and the steady-state asynchronous scheme. Both can be used to improve the convergence speed of multi-objective evolutionary algorithms (MOEAs) that rely on time-intensive fitness evaluation functions. The importance of this work stems from the fact that a correct choice for one or the other parallelization method can lead to considerable speed improvements with regards to the overall duration of the optimization. Our main aim is to provide practitioners of MOEAs with a simple but effective method of deciding which master-slave parallelization option is better when dealing with a time-constrained optimization process.
AB - This paper is focused on a comparative analysis of the performance of two master-slave parallelization methods, the basic generational scheme and the steady-state asynchronous scheme. Both can be used to improve the convergence speed of multi-objective evolutionary algorithms (MOEAs) that rely on time-intensive fitness evaluation functions. The importance of this work stems from the fact that a correct choice for one or the other parallelization method can lead to considerable speed improvements with regards to the overall duration of the optimization. Our main aim is to provide practitioners of MOEAs with a simple but effective method of deciding which master-slave parallelization option is better when dealing with a time-constrained optimization process.
KW - evolutionary computation
KW - master-slave parallelization
KW - multi-objective optimization
KW - performance comparison
KW - steady-state evolution
UR - https://www.scopus.com/pages/publications/84884401293
U2 - 10.1007/978-3-642-38610-7_12
DO - 10.1007/978-3-642-38610-7_12
M3 - Conference proceedings
SN - 978-3-642-38609-1
VL - 7895
T3 - Lecture Notes in Artificial Intelligence (LNAI)
SP - 122
EP - 134
BT - Artificial Intelligence and Soft Computing
A2 - Laszek Rutkowski and Marcin Korytkowski and Rafal Scherer and Ryszard Tadeusiewicz and Lotfi A. Zadeh and Jacek M. Zurada, null
PB - Springer Berlin Heidelberg
ER -