This proceedings volume collects contributions from the 5th AIRO Young Workshop and AIRO PhD School 2021 joint event on "Optimization and Data Science: Trends and Applications", held online, from February 8 to 12, 2021. The joint event was organized by AIROYoung representatives and the Operations Research Group of the Department of Electrical Engineering and Information Technology of the University "Federico II" of Naples. The selected contributions represent the state-of-the-art knowledge related to different branches of research, such as data science, machine learning and combinatorial…mehr
This proceedings volume collects contributions from the 5th AIRO Young Workshop and AIRO PhD School 2021 joint event on "Optimization and Data Science: Trends and Applications", held online, from February 8 to 12, 2021. The joint event was organized by AIROYoung representatives and the Operations Research Group of the Department of Electrical Engineering and Information Technology of the University "Federico II" of Naples.
The selected contributions represent the state-of-the-art knowledge related to different branches of research, such as data science, machine learning and combinatorial optimization. Therefore, this book is primarily addressed to researchers and PhD students of the operations research community. However, due to its interdisciplinary content, it will be of high interest for other closely related research communities. Moreover, this volume not only presents theoretical results but also covers real applications in computer science, engineering, economics, healthcare, and logistics, making it interesting for practitioners facing complex decision-making problems in these areas.
Adriano Masone is a Postdoctoral Researcher at the Department of Electrical Engineering and Information Technology of the University of Naples "Federico II." He obtained his PhD in Information Technology and Electrical Engineering in 2020 at the University of Naples "Federico II." In 2018-2019, he was a Visiting Scholar at the Robert H. Smith School of Business of the University of Maryland, Maryland, USA. His areas of research include exact and heuristic solutionmethods for complex combinatorial and network optimization problems with application to healthcare, transportation, logistics, production planning and scheduling, among others. Veronica Dal Sasso holds a PhD in Mathematics from the University of Padova. After the completion of the PhD, she held a postdoc at Lancaster University, where she was involved in the OptiFrame project, a project funded by the European Union under the Horizon 2020 agreement. In 2018, she moved to Rome and started working at Optrail as Operations Research Scientist. Optrail is a company devoted to providing innovative decision support solutions for the railway industry. She is the founder and current treasurer of AIROYoung, and she was part of the organizing committees for the 3rd, 4th, and 5th AIROYoungWorkshops. Valentina Morandi is an Assistant Researcher in the Science and Technology faculty at Free University of Bolzano/Bozen. She obtained her PhD in Analytics for Economics and Business in 2017 at the University of Bergamo jointly with the University of Brescia. Her research activities focus on congestion avoiding traffic assignment techniques and fair models for logistics, public transportation, and pedestrians. She teaches Operations Research in the Mechanical Engineering course, and she won the Euregio Best Young Researcher in 2019 for her research project on models for fair vehicular traffic management.
Inhaltsangabe
- Part I Data Science and Machine Learning. - Reinforcement Learning for the Knapsack Problem. - Potential Sales Estimates of a New Store. - Sells Optimization Through Product Rotation. - Part II Healthcare. - Gathering Avoiding Centralized Pedestrian Advice Framework: An Application for Covid-19 Outbreak Restrictions. - A MILP Formulation for the Reorganization of the Blood Supply Chain in Italian Regions. - Part III Logistics. - Instance Generation Framework for Green Vehicle Routing. - An Optimization Model for Service Requests Management in a 5G Network Architecture. - A MIP Model for Freight Consolidation in Road Transportation Considering Outsourced Fleet. - Part IV Optimization for Control Systems. - Energy-Oriented Inter-Vehicle Distance Optimization for Heterogeneous E-Platoons. - Optimization-Based Assessment of Initial-State Opacityin Petri Nets. - Eco-Driving Adaptive Cruise Control via Model Predictive Control Enhanced with Improved Grey Wolf. - Part V OR in Industry Optimization Algorithm. - Optimizing and Evaluating a Maintenance Strategy for Multi-Component Systems. - Metal Additive Manufacturing: Nesting vs. Scheduling. - System and Methods for Blockchain-Inspired Digital Game Asset Management.
- Part I Data Science and Machine Learning. - Reinforcement Learning for the Knapsack Problem. - Potential Sales Estimates of a New Store. - Sells Optimization Through Product Rotation. - Part II Healthcare. - Gathering Avoiding Centralized Pedestrian Advice Framework: An Application for Covid-19 Outbreak Restrictions. - A MILP Formulation for the Reorganization of the Blood Supply Chain in Italian Regions. - Part III Logistics. - Instance Generation Framework for Green Vehicle Routing. - An Optimization Model for Service Requests Management in a 5G Network Architecture. - A MIP Model for Freight Consolidation in Road Transportation Considering Outsourced Fleet. - Part IV Optimization for Control Systems. - Energy-Oriented Inter-Vehicle Distance Optimization for Heterogeneous E-Platoons. - Optimization-Based Assessment of Initial-State Opacityin Petri Nets. - Eco-Driving Adaptive Cruise Control via Model Predictive Control Enhanced with Improved Grey Wolf. - Part V OR in Industry Optimization Algorithm. - Optimizing and Evaluating a Maintenance Strategy for Multi-Component Systems. - Metal Additive Manufacturing: Nesting vs. Scheduling. - System and Methods for Blockchain-Inspired Digital Game Asset Management.
- Part I Data Science and Machine Learning. - Reinforcement Learning for the Knapsack Problem. - Potential Sales Estimates of a New Store. - Sells Optimization Through Product Rotation. - Part II Healthcare. - Gathering Avoiding Centralized Pedestrian Advice Framework: An Application for Covid-19 Outbreak Restrictions. - A MILP Formulation for the Reorganization of the Blood Supply Chain in Italian Regions. - Part III Logistics. - Instance Generation Framework for Green Vehicle Routing. - An Optimization Model for Service Requests Management in a 5G Network Architecture. - A MIP Model for Freight Consolidation in Road Transportation Considering Outsourced Fleet. - Part IV Optimization for Control Systems. - Energy-Oriented Inter-Vehicle Distance Optimization for Heterogeneous E-Platoons. - Optimization-Based Assessment of Initial-State Opacityin Petri Nets. - Eco-Driving Adaptive Cruise Control via Model Predictive Control Enhanced with Improved Grey Wolf. - Part V OR in Industry Optimization Algorithm. - Optimizing and Evaluating a Maintenance Strategy for Multi-Component Systems. - Metal Additive Manufacturing: Nesting vs. Scheduling. - System and Methods for Blockchain-Inspired Digital Game Asset Management.
- Part I Data Science and Machine Learning. - Reinforcement Learning for the Knapsack Problem. - Potential Sales Estimates of a New Store. - Sells Optimization Through Product Rotation. - Part II Healthcare. - Gathering Avoiding Centralized Pedestrian Advice Framework: An Application for Covid-19 Outbreak Restrictions. - A MILP Formulation for the Reorganization of the Blood Supply Chain in Italian Regions. - Part III Logistics. - Instance Generation Framework for Green Vehicle Routing. - An Optimization Model for Service Requests Management in a 5G Network Architecture. - A MIP Model for Freight Consolidation in Road Transportation Considering Outsourced Fleet. - Part IV Optimization for Control Systems. - Energy-Oriented Inter-Vehicle Distance Optimization for Heterogeneous E-Platoons. - Optimization-Based Assessment of Initial-State Opacityin Petri Nets. - Eco-Driving Adaptive Cruise Control via Model Predictive Control Enhanced with Improved Grey Wolf. - Part V OR in Industry Optimization Algorithm. - Optimizing and Evaluating a Maintenance Strategy for Multi-Component Systems. - Metal Additive Manufacturing: Nesting vs. Scheduling. - System and Methods for Blockchain-Inspired Digital Game Asset Management.
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