DECMO2: a robust hybrid and adaptive multi-objective evolutionary algorithm

Verfasser / Beitragende:
[Alexandru-Ciprian Zăvoianu, Edwin Lughofer, Gerd Bramerdorfer, Wolfgang Amrhein, Erich Klement]
Ort, Verlag, Jahr:
2015
Enthalten in:
Soft Computing, 19/12(2015-12-01), 3551-3569
Format:
Artikel (online)
ID: 605469229
LEADER caa a22 4500
001 605469229
003 CHVBK
005 20210128100321.0
007 cr unu---uuuuu
008 210128e20151201xx s 000 0 eng
024 7 0 |a 10.1007/s00500-014-1308-7  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00500-014-1308-7 
245 0 0 |a DECMO2: a robust hybrid and adaptive multi-objective evolutionary algorithm  |h [Elektronische Daten]  |c [Alexandru-Ciprian Zăvoianu, Edwin Lughofer, Gerd Bramerdorfer, Wolfgang Amrhein, Erich Klement] 
520 3 |a We describe a hybrid and adaptive coevolutionary optimization method that can efficiently solve a wide range of multi-objective optimization problems (MOOPs) as it successfully combines positive traits from three main classes of multi-objective evolutionary algorithms (MOEAs): classical approaches that use Pareto-based selection for survival criteria, approaches that rely on differential evolution, and decomposition-based strategies. A key part of our hybrid evolutionary approach lies in the proposed fitness sharing mechanism that is able to smoothly transfer information between the coevolved subpopulations without negatively impacting the specific evolutionary process behavior that characterizes each subpopulation. The proposed MOEA also features an adaptive allocation of fitness evaluations between the coevolved populations to increase robustness and favor the evolutionary search strategy that proves more successful for solving the MOOP at hand. Apart from the new evolutionary algorithm, this paper also contains the description of a new hypervolume and racing-based methodology aimed at providing practitioners from the field of multi-objective optimization with a simple means of analyzing/reporting the general comparative run-time performance of multi-objective optimization algorithms over large problem sets. 
540 |a Springer-Verlag Berlin Heidelberg, 2014 
690 7 |a Evolutionary computation  |2 nationallicence 
690 7 |a Hybrid multi-objective optimization  |2 nationallicence 
690 7 |a Coevolution  |2 nationallicence 
690 7 |a Adaptive allocation of fitness evaluations  |2 nationallicence 
690 7 |a Performance analysis methodology for MOOPs  |2 nationallicence 
700 1 |a Zăvoianu  |D Alexandru-Ciprian  |u Department of Knowledge-based Mathematical Systems/Fuzzy Logic Laboratory Linz-Hagenberg, Johannes Kepler University of Linz, Linz, Austria  |4 aut 
700 1 |a Lughofer  |D Edwin  |u Department of Knowledge-based Mathematical Systems/Fuzzy Logic Laboratory Linz-Hagenberg, Johannes Kepler University of Linz, Linz, Austria  |4 aut 
700 1 |a Bramerdorfer  |D Gerd  |u LCM, Linz Center of Mechatronics, Linz, Austria  |4 aut 
700 1 |a Amrhein  |D Wolfgang  |u LCM, Linz Center of Mechatronics, Linz, Austria  |4 aut 
700 1 |a Klement  |D Erich  |u Department of Knowledge-based Mathematical Systems/Fuzzy Logic Laboratory Linz-Hagenberg, Johannes Kepler University of Linz, Linz, Austria  |4 aut 
773 0 |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/12(2015-12-01), 3551-3569  |x 1432-7643  |q 19:12<3551  |1 2015  |2 19  |o 500 
856 4 0 |u https://doi.org/10.1007/s00500-014-1308-7  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00500-014-1308-7  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Zăvoianu  |D Alexandru-Ciprian  |u Department of Knowledge-based Mathematical Systems/Fuzzy Logic Laboratory Linz-Hagenberg, Johannes Kepler University of Linz, Linz, Austria  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Lughofer  |D Edwin  |u Department of Knowledge-based Mathematical Systems/Fuzzy Logic Laboratory Linz-Hagenberg, Johannes Kepler University of Linz, Linz, Austria  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Bramerdorfer  |D Gerd  |u LCM, Linz Center of Mechatronics, Linz, Austria  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Amrhein  |D Wolfgang  |u LCM, Linz Center of Mechatronics, Linz, Austria  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Klement  |D Erich  |u Department of Knowledge-based Mathematical Systems/Fuzzy Logic Laboratory Linz-Hagenberg, Johannes Kepler University of Linz, Linz, Austria  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/12(2015-12-01), 3551-3569  |x 1432-7643  |q 19:12<3551  |1 2015  |2 19  |o 500