
This book presents an overview of archiving strategies developed over the last years by the authors that deal with suitable approximations of the sets of optimal and nearly optimal solutions of multi-objective optimization problems by means of stochastic search algorithms. All presented archivers are analyzed with respect to the approximation qualities of the limit archives that they generate and the upper bounds of the archive sizes. The convergence analysis will be done using a very broad ...
DETAILS
Archiving Strategies for Evolutionary Multi-objective Optimization Algorithms
Schütze, Oliver, Hernández, Carlos
Kartoniert, xiii, 234 S.
XIII, 234 p. 130 illus., 44 illus. in color.
Sprache: Englisch
235 mm
ISBN-13: 978-3-030-63775-0
Titelnr.: 95410479
Gewicht: 385 g
Springer, Berlin (2022)
Herstelleradresse
Springer Heidelberg
Tiergartenstr. 17
69121 - DE Heidelberg
E-Mail: buchhandel-buch@springer.com