Visualization and Performance Metric in Many-Objective Optimization

Visualization of population in a high-dimensional objective space throughout the evolution process presents an attractive feature that could be well exploited in designing many-objective evolutionary algorithms (MaOEAs). In this paper, a new visualization method is proposed. It maps individuals from...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE transactions on evolutionary computation Ročník 20; číslo 3; s. 386 - 402
Hlavní autoři:	Zhenan He, Yen, Gary G.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.06.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Approximation Approximation methods Dominance Evolutionary algorithms Evolutionary design method Heating many-objective evolutionary algorithm many-objective optimization problem mapping Measurement Pareto optimality Performance measurement performance metric Quality assessment Shape Sociology Statistics Visualization performance metric mapping visualization many-objective optimization problem (MaOP) Many-objective evolutionary algorithm (MaOEA)
ISSN:	1089-778X, 1941-0026
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!