Operations Research and Data Science in Public Services: 6th AIROYoung Workshop, Rome, Italy, February 23–25, 2022 (AIRO Springer Series, 11)

This book provides a collection of contributions by Ph.D. students and early researchers who attended the 6th AIROYoung Workshop, held in Rome (Italy) at Roma Tre University, from 23 February to 25 February 2022. The selected contributions represent state-of-the-art knowledge related to several areas of operations research, optimization, and data science. The target audience of this book is primarily composed of Ph.D. students and early or experienced researchers in optimization and operations research. However, due to its interdisciplinary content, it is of high interest to other closely related research communities. Moreover, since it contains several works involving the use of optimization and data science in real applications, it is of interest to practitioners facing complex decision-making problems in these areas. Organization Preface Contents Editors and Contributors Predicting the Empirical Hardness of Metric TSP Instances 1 Introduction 2 Cost Features of the Metric TSPs 3 Learning Decision Trees 4 Computational Results 5 Conclusions and Future Perspectives References A Two-Phase Approach to Evaluate and Optimize an Interlibrary Loan Service: The Case Study of Provincia di Brescia 1 Introduction and Motivation 2 The Interlibrary Loan Service of Provincia di Brescia 3 Related Work 4 A Two-Phase Approach 4.1 Phase 1: Clustering 4.2 Phase 2: Routing 5 Experimental Evaluation 5.1 Application of Phase 1: Clustering 5.2 Instances 5.3 Application of Phase 2: Routing 6 Discussion and Conclusions References Optimising the Order Picking Process: The Case of a Retail Distribution Company in Italy 1 Introduction 2 Mathematical Model 3 Computational Results 3.1 Case of Study 3.2 Numerical Results 4 Conclusions and Future Works References Batch Delivery Considerations in Additive Manufacturing Machine Scheduling Problem 1 Introduction 2 Related Work 3 Problem Definition 4 Proposed GA Approach 5 Numerical Results 6 Conclusions References An LP Model for the Central Energy System 1 Introduction 2 Literature Review 3 Methodology 4 Numerical Tests 5 Conclusions and Future Developments References Author Index Subject Index