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Optimization in Artificial Intelligence and Data Sciences = ODS, First Hybrid Conference, Rome, Italy, September 14-17, 2021 /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimization in Artificial Intelligence and Data Sciences/ edited by Lavinia Amorosi, Paolo Dell’Olmo, Isabella Lari.
Reminder of title:	ODS, First Hybrid Conference, Rome, Italy, September 14-17, 2021 /
other author:	Amorosi, Lavinia.
Description:	XIII, 267 p. 41 illus., 24 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Mathematical optimization. -
Online resource:	https://doi.org/10.1007/978-3-030-95380-5
ISBN:	9783030953805

Optimization in Artificial Intelligence and Data Sciences = ODS, First Hybrid Conference, Rome, Italy, September 14-17, 2021 /
Optimization in Artificial Intelligence and Data SciencesODS, First Hybrid Conference, Rome, Italy, September 14-17, 2021 /[electronic resource] :edited by Lavinia Amorosi, Paolo Dell’Olmo, Isabella Lari. - 1st ed. 2022. - XIII, 267 p. 41 illus., 24 illus. in color.online resource. - AIRO Springer Series,82523-7055 ;. - AIRO Springer Series,1.

1 Mauro Passacantando and Fabio Raciti, A variational inequality approach to a class of network games with local complementarities and global congestion -- 2 Patrizia Daniele and Daniele Sciacca, A two-stage Variational Inequality formulation for a Game Theory Network Model for hospitalization in critic scenarios -- 3 Lorenzo Lampariello et al., On nested affine variational inequalities: the case of multi-portfolio selection -- 4 Rosita Guido et al., Hyper-Parameter Optimization in Support Vector Machine on unbalanced datasets using Genetic Algorithms -- 5 Giovanni Fasano and Massimo Roma, An improvement of the pivoting strategy in the Bunch and Kaufman decomposition, within Truncated Newton methods -- 6 Giulia Caselli et al., Mixed Integer Linear Programming for a Real-World Parallel Machine Scheduling Problem with Workforce and Precedence Constraints -- 7 Lavinia Amorosi et al., Scheduling K-mers Counting in a Distributed Environment -- 8 Nicolas Zufferey et al., Workload balancing at cross-docking platforms -- 9 Giovanni Righini and Pier Giorgio Villani, Knowledge before solutions: some reflections on a successful O.R. case study -- 10 Luigi Rarità, A genetic algorithm to optimize dynamics of supply chains -- 11 Georgia Fargetta and Laura Scrimali, Closed-Loop Supply Chain Network Equilibrium with online second-hand trading -- 12 Andrea Bettinelli et al., Design and optimization of a regional buffalo milk supply chain: a case study -- 13 Olivier Gallay et al., Truck-and-drone parcel delivery in the Alps -- 14 Giacomo Lanza et al., A fast heuristic approach for the assignment and sequencing storage location problem under a two level storage policy -- 15 Nicolas Zufferey et al., Local Search for Aircraft-Landing Planning -- 16 Annamaria Barbagallo, An Emission Pollution Permit System for Time-Dependent Transportation Networks Based on Origin-Destination Pairs -- 17 Daniel Bienstock et al., Power network design with line activity -- 18 Vassil Vassilev et al., Risk Assessment in Transactions under Threat as Partially Observable Markov Decision Process -- 19 Paola Cappanera et al., A decomposition approach to the Clinical Pathway Deployment for chronic outpatients with comorbidities -- 20 Fulvio De Santis and Stefania Gubbiotti, Optimal sample size for evidence and consensus in phase III clinical trials -- 21 Roberto Aringhieri et al., Novel applications of the team orienteering problem in health care logistics -- 22 Beatrice Bolsi et al., Optimizing a Dynamic Outpatient Facility System with Multiple Servers -- 23 Pranath Kumar Gourishetty et al., Global optimization of a turbine design via neural networks and an evolutionary algorithm. .

This book is addressed to researchers in operations research, data science and artificial intelligence. It collects selected contributions from the first hybrid “Optimization and Decision Science - ODS2021” international conference on the theme Optimization and Artificial Intelligence and Data Sciences, which was held in Rome 14-17 September 2021 and organized by AIRO, the Italian Operations Research Society and the Department of Statistical Sciences of Sapienza University of Rome. The book offers new and original contributions on different methodological optimization topics, from Support Vector Machines to Game Theory Network Models, from Mathematical Programming to Heuristic Algorithms, and Optimization Methods for a number of emerging problems from Truck and Drone delivery to Risk Assessment, from Power Networks Design to Portfolio Optimization. The articles in the book can give a significant edge to the general themes of sustainability and pollution reduction, distributive logistics, healthcare management in pandemic scenarios and clinical trials, distributed computing, scheduling, and many others. For these reasons, the book is aimed not only at researchers in the Operations Research community but also for practitioners facing decision-making problems in these areas and to students and researchers from other disciplines, including Artificial Intelligence, Computer Sciences, Finance, Mathematics, and Engineering.

ISBN: 9783030953805

Standard No.: 10.1007/978-3-030-95380-5doiSubjects--Topical Terms:

527675
Mathematical optimization.

LC Class. No.: QA402.5-402.6

Dewey Class. No.: 519.6

Optimization in Artificial Intelligence and Data Sciences = ODS, First Hybrid Conference, Rome, Italy, September 14-17, 2021 /
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