Operations Research: Closing the Gap Between Research and Practice: International Conference on Optimization and Decision Science (ODS), Badesi, Italy, September 8-12, 2024

by Massimo Di Francesco (Editor), Enrico Gorgone (Editor), Benedetto Manca (Editor), Simone Zanda (Editor)

Overview

This book collects selected contributions of the “Optimization and Decision Science - ODS2024 - International conference on the theme of Operations Research: closing the gap between research and practice ODS2024 was held in Badesi (Sardinia, Italy), 8–12 September 2024, and was organized by AIRO, the Italian Operations Research Society. The book offers new and original contributions on operations research, optimization, decision science, and prescriptive analytics from both a methodological and applied perspectives. It provides a state-of-the art on problem models and solving methods to address a widely class of real-world problems, arising in different application areas such as logistics, transportation, energy management, manufacturing, health, ICT and mobile networks, and emergency/disaster management. In addition, the scientific works collected in this book aim at providing significant contributions in the theme of a close connection between research and practice. This book is aimed primarily at researchers and Ph.D. students in the Operations Research community. However, due to its interdisciplinary contents, this book is of high interest also for students and researchers from other disciplines, including artificial intelligence, computer sciences, finance, mathematics, and engineering as well as for practitioners facing complex decision-making problems in logistics, manufacturing production, and services.

Product Details

ISBN-13:	9783031900945
Publisher:	Springer Nature Switzerland
Publication date:	09/29/2025
Series:	AIRO Springer Series , #15
Pages:	349
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

The editors are members of the Operations Research group of the University of Cagliari with expertises in Logistics, Machine Learning and Non-Smooth Optimization. Massimo di Francesco and Enrico Gorgone are associate professors and Benedetto Manca e Simone Zanda are assistant professors. All of them organized the Optimization and Decision Science Conference 2024 held in Badesi (Sardinia, Italy). They collaborate with other researchers in the optimization filed, especially with researchers from the CIRRELT group in Canada, the University of Calabria, the University of Pisa and the Ecole Polytechnique in Paris.

Table of Contents

Towards Safer Freight Rail Shunting: Integrating MILP and ML Classification Models in a Risk Management Framework.- Optimisation of reinforcement learning Forex trading algorithms based on technical indicators.- On the approximation of the Shapley value via machine learning in transportation network cooperative games.- The Cost-benefit Trade-off between Problem-specific and Algorithm-specific Meta-learning for the Knapsack Problem.- Customizing characteristics of multi-queue multi-server systems.- Delay Constrained Routing: the Multi-Flow Single-Path Case.- A robustness analysis of trading strategy ensembling based on trader preferences.- Intervention Planning for a Home Health-and-Social-Care Institute in Switzerland.- Inventory Policy for Perishable Products with Diminishing Freshness.- Unassigned distance geometry and the Buckminsterfullerene.- Stop-skipping to Reduce Delays in Train Rescheduling.- On the distribution of the random risk under alternative loss functions.- A Mixed-integer Linear Program to create the shifts in a supermarket.- A greedy heuristic for the equitable allocation of edible surplus food.- Probabilistic branch-and-bound for clusterwise linear regression.- Lower Bounds and a Constraint Programming Approach for Scheduling an Assembly Problem with Precedence and Resource Constraints.- Complexity results on the Bi-level Interdiction Knapsack Problem with unit interdiction costs or unit weights.- Shutdown Maintenance Scheduling using Two-Stage Shastic Programming with Endogenous Uncertainty.- Scheduling carbon dioxide transfers between two ports via mixed-integer linear programming and heuristic approaches.- Railway Wheel Impact Force and Alert Prediction using Machine Learning Models.- Graph Convolutional Neural Network Assisted Monte Carlo Tree Search for the Capacitated Vehicle Routing Problem with Time Windows.- QoS Estimation in Schedule-Based Vaccination Clinics.- Integrated optimization of building and curing in tires production.- Extended formulations for the Electric Asymmetric TSP.- Optimization of nutrition for I.C.U. patients.- A Branch & Bound algorithm for the Rainbow Spanning Forest Problem.- Application of Artificial Intelligence Techniques in Battery Energy Storage Systems Optimization.- On Multiple Agents Dealing with Multiple Criteria via the Hypervolume Approach.- Existence and approximation results for Quasi Variational Inequalities with linear coupling constraints.- A comparison of solution approaches for the port rail shunting optimization: a case study.- Two-dimensional irregular knapsack problem with defects from a dynamic textile environment.- The Ellipsoidal Separation Machine.- Lagrangian Relaxation for the Intermediate Facilities Location problem.