7. Worst-case complexity analysis of a-posteriori methods for multi-objective optimization
Invited abstract in session TC-10: Continuous Multi-Objective Optimization: Algorithms and Complexity Analyses, stream Multiobjective and Vector Optimization.
Tuesday, 14:00-16:00Room: B100/8011
Authors (first author is the speaker)
| 1. | Giampaolo Liuzzi
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| DIAG, Sapienza Univ. of Rome | |
| 2. | Andrea Cristofari
|
| Department of Civil Engineering and Computer Science Engineering, University of Rome "Tor Vergata" | |
| 3. | Marianna De Santis
|
| University of Florence | |
| 4. | Stefano Lucidi
|
| Department of Computer, Control, and Management Science, University of Rome "La Sapienza" |
Abstract
In this work, we consider unconstrained a-posteriori multi-objective optimization problems. The main aim of the work is to give worst-case complexity bounds for multi-objective optimization methods which adopt a linesearch technique along steepest descent directions. We show that the considered methods enjoy the same worst-case complexity bounds recently proved in the literature for derivative-free methods.
Keywords
- Multi-objective optimization
Status: accepted
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