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15 Jan 2021
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29 Jan 2021
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Corso di dottorato "Heuristic algorithms for Combinatorial Optimization problems"
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Nelle prossime settimane terro' in videoconferenza un corso di 20 ore dedicato a una panoramica degli algoritmi euristici per problemi di Ottimizzazione Combinatoria.
Il corso si tiene nell'ambito del dottorato di Informatica dell'Universita' degli Studi di Milano.
Le date previste (soggette a possibili cambiamenti) e gli argomenti sono:
15/01/2021 14:00-17:00 Generalita'
18/01/2021 14:00-17:00 Valutazione teorica ed empirica
19/01/2021 14:00-17:00 Euristiche e metaeuristiche costruttive (GRASP, Ant System)
22/01/2021 14:00-17:00 Euristiche di scambio
25/01/2021 14:00-17:00 Metaeuristiche di scambio (ILS,VNS,VND)
27/01/2021 14:00-17:00 Metaeuristiche di scambio (TS, SA)
29/01/2021 14:00-17:00 Metaeuristiche di ricombinazione (SS, PR, algoritmi genetici)
Dettagli e materiali saranno via via pubblicati sulla mia pagina web.
Roberto Cordone
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Online, Università degli Studi di Milano |
Italy |
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26 Nov 2020
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26 Nov 2020
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Analysis and Interventions in Large Network Games: Graphon Games and Graphon Contagion
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November 26, 2020, h 17:00
Speaker: Francesca Parise
Discussants: Giacomo Como, Daniel Cooney, Mathieu Lauriere.
Click here to access the Virtual Room: http://mailsender.luiss.it/lists/lt.php?id=cRpRCgYHSAUHAAFOVgFdBQs
The papers can be found here:
https://arxiv.org/abs/1802.00080
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3674691
Information about future seminars can be found here:
https://economiaefinanza.luiss.it/seminari/prossimi-seminari
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Online, LUISS, Rome |
Italy |
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27 Oct 2020
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29 Oct 2020
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"Conic, especially copositive optimization" by Prof. I. M. Bomze
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Timetable: 8 hrs.
The course will be held online (link Zoom will be comunicated).
Calendar of the lectures
Tuesday October 27, 2020, 16:00
Wednesday October 28, 2020, 10:00-12:00
Thursday October 29, 2020, 10:00-12:00 and 15:00-17:00
Speaker: Prof. I. M. Bomze
Title: Conic, especially copositive optimization
Course contents.
Quite many combinatorial and some important non-convex continuous optimization
problems admit a conic representation, where the complexity of solving non-
convex programs is shifted towards the complexity of sheer feasibility (i.e.,
membership of the cone which is assumed to be a proper convex one), while
structural constraints and the objective are all linear. The resulting problem
is therefore a convex one, and still equivalent to some NP-hard problems with
inefficient local solutions despite the fact that in the conic formulation,
all local solutions are global.
Using characterizations of copositivity, one arrives at various
approximations. However, not all of these are tractable with current
technology. In this course, we will address some approaches on which tractable
SDP- or LP-approximations, and also branch-and-bound schemes, may be based.
This way, good tractable bounds can be achieved which serve as quality control
for any primal-feasible algorithm. But which one should be employed?
Complementing above (dual) approach, we will, mainly as one example, address a
classical yet not widely known first-order approach for poly/posynomial
optimization under simplex constraints, embedded in some general optimization
principles for iterative primal methods.
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Online, University of Padova |
Italy |
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