Optimization and Data Science: Trends and Applications: 5th AIROYoung Workshop and AIRO PhD School 2021 Joint Event (AIRO Springer Series Book 6)

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. Preface 6 Contents 10 About the Editors 12 Part I Data Science and Machine Learning 13 Reinforcement Learning for the Knapsack Problem 14 1 Introduction 14 2 Problem Formulation and Background Information 15 2.1 Reinforcement Learning Framework 16 2.1.1 Double Q-Learning 17 2.1.2 Learning Strategy 18 2.2 The Agent 19 2.2.1 Self-Attention, Multi-Head, and Multi-Layer Transformer 20 2.3 Model Architecture 21 3 Computational Results 21 4 Conclusion 23 References 24 Potential Sales Estimates of a New Store 25 1 Introduction and Problem Definition 25 2 Geospatial DB Creation and Geospatial Features 26 2.1 The Geospatial Database 26 2.2 The Geospatial Features 27 3 Proposed Machine Learning (ML) Based Approach 29 3.1 CNN and Satellite Pictures 29 3.2 GBM for Geospatial Features Based Potential Prediction 31 4 Results of the Proposed ML Approach 32 5 Conclusions 33 References 33 Sells Optimization Through Product Rotation 35 1 Introduction and Problem Description 35 2 Solution Approach 38 3 Sale Prediction of VMs 40 4 Problem Formulation 42 5 Computational Results 44 6 Conclusions 45 References 46 Part II Healthcare 47 Gathering Avoiding Centralized Pedestrian Advice Framework: An Application for Covid-19 Outbreak Restrictions 48 1 Introduction 48 1.1 Literature Review 49 2 The Gathering Avoiding Pedestrian Routing Model 51 2.1 Solution Method 53 3 Computational Results 53 3.1 Performance of the Model 55 4 Conclusions and Future Research 57 References 58 A MILP Formulation for the Reorganization of the Blood Supply Chain in Italian Regions 59 1 Introduction 60 2 MILP Model for the Reorganization of a Regional BSC 62 3 Application of the Model to the Case of the BSC of the Campania and Puglia Regions 67 3.1 Test Case Description 68 3.2 Experimental Results 69 4 Conclusions 72 References 73 Part III Logistics 75 Instance Generation Framework for Green Vehicle Routing 76 1 Introduction 76 2 Literature Review 77 3 Problem Definition 78 4 Instance Generation Framework 79 5 Computational Experiments 83 6 Conclusions 84 References 85 An Optimization Model for Service Requests Management in a 5G Network Architecture 87 1 Introduction 87 2 The Model 88 3 Variational Formulation 96 4 An Illustrative Numerical Example 99 5 Conclusion 102 References 103 A MIP Model for Freight Consolidation in Road Transportation Considering Outsourced Fleet 105 1 Introduction 105 2 Problem Description 107 3 Mathematical Formulation 108 4 Computational Experiments 111 5 Concluding Remarks 114 References 115 Part IV Optimization for Control Systems 116 Energy-Oriented Inter-Vehicle Distance Optimization for Heterogeneous E-Platoons 117 1 Introduction 118 2 Problem Statement 119 2.1 Autonomous Electric Vehicles Longitudinal Dynamics 119 2.2 Battery Model 120 2.3 Power-Based Energy Consumption Estimation Model 121 3 Optimization Procedure 122 4 Numerical Results 124 5 Conclusion 127 References 127 Optimization-Based Assessment of Initial-State Opacity in Petri Nets 130 1 Introduction 131 2 Backgrounds 132 2.1 Basic Petri Nets notation 132 2.2 Initial State Opacity in Petri Nets 135 3 Main Results 136 4 Examples 138 5 Conclusions 140 References 140 Eco-Driving Adaptive Cruise Control via Model Predictive Control Enhanced with Improved Grey Wolf Optimization Algorithm 142 1 Introduction 142 2 Mathematical Preliminaries 144 2.1 Grey Wolf Optimizer 144 2.1.1 Grey Wolf Optimizer: Principle of Operation 144 2.1.2 Encircling 144 2.1.3 Hunting 144 2.1.4 Attacking 145 2.2 Improved Grey Wolf Optimizer: IGWO 145 3 Problem Statement 146 3.1 Electric Autonomous Ego Vehicle 147 3.2 Control Objectives 148 4 Control Design 148 4.1 Nonlinear Model Predictive Control Design 149 4.2 Grey Wolf Optimization Algorithm for the Tuning of the NMPC Weights 150 5 Numerical Analysis 151 5.1 Numerical Results 152 5.2 Comparison Analysis 152 6 Conclusion 154 References 155 Part V OR in Industry 157 Optimizing and Evaluating a Maintenance Strategy for Multi-Component Systems 158 1 Introduction 158 2 Mathematical Modelling of the Problem 159 2.1 Maintenance Policy 160 3 Expected Cost Definition 160 4 Optimization Algorithms 162 4.1 Local Search 162 4.2 Meta-Heuristic Algorithms 163 4.2.1 Genetic Algorithms 163 4.2.2 Pattern Search 164 4.2.3 Ant Colony Algorithm 164 5 Case Study 165 5.1 Identical Degrading Components 165 5.2 Non-Identical Degrading Components 167 6 Conclusions 168 References 169 Metal Additive Manufacturing: Nesting vs. Scheduling 170 1 Introduction 170 2 Literature Review 171 3 Problem Statement 172 4 Solution Methodology 175 5 Numerical Examples 177 6 Conclusion and Future Research 179 A.1 Appendix 180 References 181 System and Methods for Blockchain-Inspired Digital Game Asset Management 182 1 Context and Concepts 182 2 TCA 183 2.1 Scenario 183 2.2 Actors and Concepts 185 2.3 Transactions 185 3 Security Features 188 4 Conclusion 188 References 189