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), 812 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.
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 Stochastic 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.
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.
