Fast Implementation of the Steady-State NSGA-II Algorithm for Two Dimensions Based on Incremental Non-Dominated Sorting

Maxim Buzdalov, Ilya Yakupov, Andrey Stankevich

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

Crynodeb

Genetic algorithms (GAs) are widely used in multi-objective optimization for solving complex problems. There are two distinct approaches for GA design: generational and steady-state algorithms. Most of the current state-of-the-art GAs are generational, although there is an increasing interest to steady-state algorithms as well. However, for algorithms based on non-dominated sorting, most of steady-state implementations have higher computation complexity than their generational counterparts, which limits their applicability. We present a fast implementation of a steady-state version of the NSGA-II algorithm for two dimensions. This implementation is based on a data structure which has O(N) complexity for single solution insertion and deletion in the worst case. The experimental results show that our implementation works noticeably faster than steady-state NSGA-II implementations which use fast non-dominated sorting.
Iaith wreiddiolSaesneg
TeitlGECCO '15
Is-deitlProceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation
GolygyddionSara Silva
CyhoeddwrAssociation for Computing Machinery
Tudalennau647-654
Nifer y tudalennau8
ISBN (Argraffiad)978-1-4503-3472-3
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 11 Gorff 2015
Cyhoeddwyd yn allanolIe
Digwyddiad16th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Sbaen
Hyd: 11 Gorff 201515 Gorff 2015

Cynhadledd

Cynhadledd16th Genetic and Evolutionary Computation Conference, GECCO 2015
Gwlad/TiriogaethSbaen
DinasMadrid
Cyfnod11 Gorff 201515 Gorff 2015

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