Fwd: SPS Tutorial by Francesca Maggioni on Nov 8

[Alice Raffaele]

Dear AIROYoungers,

I am forwarding you the announcement of an interesting tutorial by Francesca Maggioni tomorrow. The talk title is “Bounding multistage optimization problems under uncertainty” and will be held on Zoom.

Best,

Alice

---------- Forwarded message ---------
From: Francesca MAGGIONI <francesca...@unibg.it>
Date: Wed, 6 Nov 2024 at 22:25
Subject: Fwd: SPS Tutorial by Francesca Maggioni on Nov 8
To: Alice Raffaele <alice.r...@gmail.com>

Cara Alice,

spero tutto bene. Inoltro il tutorial qui sotto nel caso possa essere utile per Airo Young.

Grazie,

Un caro saluto e a presto,
Francesca

_______________________________________________________

Francesca Maggioni, PhD

Professor of Operations Research (ssd MATH-06/A)

Department of Management, Information and Production Engineering

University of Bergamo, Via Marconi - 5 24044 Dalmine, (Bg) Italy

Chair of the European Working Group on Stochastic Optimization (EWGSO)

Tel: +39-035-2052649, Home-page: www.francescamaggioni.it

________________________________________________________

---------- Forwarded message ---------
Da: Merve Bodur <merve...@ed.ac.uk>
Date: mar 5 nov 2024 alle ore 14:58
Subject: SPS Tutorial by Francesca Maggioni on Nov 8
To: <STOPROG-...@maillist.usc.edu>

Date: Nov 8, 2024 Time: 10-11am ET Speaker: Francesca Maggioni Talk Title: Bounding multistage optimization problems under uncertainty Zoom Information: (Please do not publicly share this information, instead, recommend anyone interested to

Date: Nov 8, 2024

Time: 10-11am ET

Speaker: Francesca Maggioni

Talk Title: Bounding multistage optimization problems under uncertainty

Zoom Information: (Please do not publicly share this information, instead, recommend anyone interested to sign up to our mailing list following the instructions on our seminar website)

• Link: LINK
• Passcode: 962 0896 9117
• Meeting ID: 583833

Talk Abstract: Many real world decision problems are dynamic and affected by uncertainty.  Stochastic Programming provides a powerful approach to handle this uncertainty within a multi-period decision framework. However, as the number of stages increases, these problems become challenging to solve due to their rapid growth in complexity. To tackle this, approximation techniques are often used to simplify the original problem, providing useful upper and lower bounds for the objective function’s optimal value.

This tutorial explores several methods for generating bounds in multistage optimization problems under uncertainty. We begin by reviewing bounds based on distribution and function approximations, drawing from established literature, and illustrating their connection to the "generalized moment problem". Next, we discuss bounds based on scenario grouping under the assumption that a sufficiently large scenario tree is given but is unsolvable, both in the context of stochastic programming and distributionally robust optimization. Finally, guaranteed bounds based on the concepts of first order and convex order stochastic dominance are presented. These approximations are versatile, applying to a wide range of problems without requiring specific conditions like linearity, convexity, or stagewise independence. Our tutorial aims to highlight current research gaps and inspire further investigation into promising directions within this field.

Speaker Bio: Francesca Maggioni is Professor of Operations Research at the Department of Management, Information and Production Engineering (DIGIP) of the University of Bergamo (Italy). She graduated summa con laude in 2003 in Mathematics at the “Università Cattolica del Sacro Cuore” of Brescia (Italy) and completed her PhD in Pure and Applied Mathematics at University of Milano Bicocca (Italy), in 2006. Her research interests concern both methodological and applicative aspects for optimization under uncertainty. From a methodological point of view, she has developed different types of bounds and approximations for stochastic, robust and distributionally robust multistage optimization problems. She applies these methods to solve problems in logistics, transportation, energy and machine learning. On these topics she has published more than 60 scientific articles featured in peer-reviewed operations research journals. In 2021 her research has been supported as principal investigator by a grant from the Italian Ministry of Education for the project “ULTRA OPTYMAL Urban Logistics and sustainable TRAnsportation: OPtimization under uncertainTY and MAchine Learning”. She currently chairs the EURO Working Group on Stochastic Optimization and the AIRO Thematic Section of Stochastic Programming. She has been secretary and treasurer of the Stochastic Programming Society. She is Associate Editor of the journals Transportation Science, Computational Management Science (CMS), EURO Journal on Computational Optimization (EJCO), TOP, International Transactions in Operational Research (ITOR), Networks and guest editor of several special issues in Operations Research and Applied Mathematics journals.

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More information and upcoming seminars can be found in the SPS Seminar Series Website.

Seminar recordings can be found on the SPS Youtube Channel. 

For questions, please feel free to contact the organizers: Merve Bodur and Giorgio Consigli.

The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th’ ann an Oilthigh Dhùn Èideann, clàraichte an Alba, àireamh clàraidh SC005336.