PLAN RADA SEMINARA ZA JUN 2024. GODINE
Predavanja na seminaru mogu se pratiti na daljinu preko linka
https://miteam.mi.sanu.ac.rs/asset/wnz6oyxsQsy29LfJA.
Registracija za on-line praćenje predavanja na Seminaru je na linku
https://miteam.mi.sanu.ac.rs/asset/xzGqvSp7aWbg8WpYX.
Neulogovani korisnici mogu pratiti prenos predavanja na ovom linku (ali ne mogu postavljati pitanja osim putem chata):
https://miteam.mi.sanu.ac.rs/call/wnz6oyxsQsy29LfJA/MjQ__eH607WeAL9X7IFtUI98xdQQgVkp-ljiEKPPfXr.
Utorak, 04.06.2024. u 14:00, Kneza Mihaila 36, sala 301f i
Online
Adam Skalski, Mathematical Institute of the Polish Academy of Sciences, Warsaw
(MAXIMAL) HAAGERUP PROPERTY FOR GROUPS AND OPERATOR ALGEBRAS
The talk will be divided into two parts: the first will have an introductory character: we will discuss how one associates to a discrete group a von Neumann algebra, and explain how the approximation properties for a discrete group (such as say amenability or the Haagerup property) can be reflected via the properties of the algebra in question. We will also spend some time explaining the origins and motivations behind the study of approximation properties of operator algebras, focusing on the Haagerup property.
In the second part of the talk we will present some results regarding concrete examples of maximal Haagerup subgroups and von Neumann subalgebras, obtained in joint work with Yongle Jiang.
Utorak, 11.06.2024. u 14:15, Online
Jasmina Pivar, Department of Informatics, Faculty of Economics & Busines, University of Zagreb
ADOPTION OF BIG DATA TECHNOLOGIES IN EU SMART CITIES
This research connects fields of smart cities and big data technologies by identifying factors influencing the adoption of big data technologies in European Union cities. The objective was to identify and evaluate factors that influence the adoption of big data technologies. Survey was carried out. The target population were cities of the European Union - EU28 countries with more than 40 thousand inhabitants. PLS-SEM was used to evaluate the model. Technological Readiness, Absorption Capacity, City Management Support, Existence of Smart City Strategy and Stakeholder Support were identified as factors that directly influence the Adoption of big data technologies in cities.
Utorak, 18.06.2024. u 14:15, Knez Mihailova 36, sala 301f i
Online
Maria Alessandra Montenegro, Fakultet organizacionih nauka
MODEL UPRAVLJANJA REZILIJENTNOŠĆU PROJEKTA
Brojni poremećaji koji su zadesili svet poslednjih nekoliko godina, poput Covid-19 pandemije, doveli su do brojnih oštećenja organizacija širom sveta. Veliki problem uočava se u situacijama kada u okruženju dođe do pojave poremećaja koga nije bilo moguće predvideti. Za suočavanje sa ovakvim izazovima, novija literatura predlaže korišćenje pristupa upravljanje rezilijentnosću projekta. Predmet istraživanja doktorske disertacije je razvoj modela upravljanja rezilijentnošću projekta koji predstavlja sveobuhvatno rešenje za efikasnije upravljanje projektima u situacijama pojave nepredvidivih poremećaja. Evaluacija razvijenog modela rađena je kroz dve faze. Rezultati istraživanja su potvrdili da postoji statistički značajna razlika između grupa ispitanika na čijim su projektima primenjivani elementi predloženog modela u odnosu na grupu ispitanika na čijim projektima isti nisu primenjivani. Kao glavni rezultati istraživanja navode se da model upravljanja rezilijentnosću projekta obuhvata sve elemente koncepta upravljanja rezilijentnosću prilagođene konceptu upravljanja projektom, da model sadrži metode za planiranje i implementaciju odgovora na nepredvidive poremećaje i metode za oporavak projekta od dejstva nepredvidivih poremećaja, da model podrazumeva primenu u različitim domenima rezilijentnosti projekta i da kao takavom ogućava organizacijama efikasnije upravljanje projektima uprkos pojavi nepredvidivih poremećaja.
Utorak, 25.06.2024. u 14:15, Online
Angelo Sifaleras, Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
REINFORCEMENT LEARNING ENHANCED METAHEURISTICS: A CASE STUDY WITH VARIABLE NEIGHBORHOOD SEARCH
This presentation introduces a new hyperheuristic approach which combines Reinforcement Learning and Variable Neighborhood Search (VNS) and it is called Bandit VNS, in order to improve solutions for the Capacitated Vehicle Routing Problem (CVRP). The Multi-Armed Bandit framework, refined by the UCB algorithm, dynamically selects the most promising neighborhood structures, addressing the challenge of identifying the optimal sequence of local search operators. Adaptive Windowing enhances the system's responsiveness to the evolving optimization landscape. Our comprehensive analysis includes evaluating various UCB algorithm modifications and incorporating parallel computing paradigms that augment Bandit VNS. Empirical validations conducted on benchmark CVRP instances highlight a 25% enhancement in solution quality when compared to the conventional General Variable Neighborhood Search method using standard library instances of medium and large size. Our research sets a precedent for future explorations into AI-driven metaheuristics, promising advancements in optimization theory and practice.
This is a joint work by: Panagiotis Kalatzantonakis, Angelo Sifaleras, and Nikolaos Samaras, all from the Department of Applied Informatics, of the University of Macedonia, Thessaloniki, Greece. The talk will mainly summarize the findings of the paper: [Kalatzantonakis P., Sifaleras A., and Samaras N., "A reinforcement learning - variable neighborhood search method for the capacitated vehicle routing problem", Expert Systems with Applications, Elsevier, Vol. 213, Article ID 118812, 2023.], but will also discuss about potential future work.
Zajednički sastanak sa AI seminarom.
RUKOVODIOCI SEMINARA
MI SANU
Vera Kovačević-Vujčić
Milan Dražić
FON
Zorica Bogdanovic
Marijana Despotovic-Zrakic
IEEE
Bozidar Radenkovic
