Lecture Notes in Computer Science Series ; ; v.14754
Altri autori (Persone)
OlteanuAlexandru-Liviu
PardoEduardo G
SifalerasAngelo
MakboulSalma
Lingua di pubblicazione
Inglese
Formato
Materiale a stampa
Livello bibliografico
Monografia
Nota di contenuto
Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- General Papers -- Learning Sparse-Lets for Interpretable Classification of Event-interval Sequences -- 1 Introduction -- 2 Related Work -- 2.1 Distance-Based Embedding -- 2.2 Feature-Based Embedding -- 3 Background -- 3.1 Event Table and E-Lets -- 4 Methodology -- 4.1 Genetic Algorithm -- 5 Experimental Evaluation -- 5.1 Hyper-parameters Tuning -- 5.2 BRKGA Settings -- 5.3 Computational Results -- 6 Conclusions -- References -- Deep Reinforcement Learning for Smart Restarts in Exploration-Only Exploitation-Only Hybrid Metaheuristics -- 1 Introduction -- 2 Background -- 2.1 The UES-CMAES Exploration-Only Exploitation-Only Hybrid -- 2.2 Hybridization of Machine Learning with Metaheuristics -- 3 Restarts as a Reinforcement Learning Problem -- 3.1 The Environment -- 3.2 The Agent -- 4 Assessing the Agent's Performance -- 4.1 On Individual Functions -- 4.2 On the Entire Benchmark -- 5 Optimization Results -- 5.1 Benchmark-Wide Performance -- 5.2 Comparison Against Other Algorithms -- 6 Conclusions and Future Work -- References -- Optimization of a Last Mile Delivery Model
with a Truck and a Drone Using Mathematical Formulation and a VNS Algorithm -- 1 Introduction -- 2 Model Description -- 3 Solution Method: VNS Algorithm -- 3.1 Construction of Initial Solution -- 3.2 Neighborhood Structures -- 3.3 Local Search Strategy -- 4 VNS with Cumulative Gain Approach (G-VNS) -- 5 Numerical Experiments -- 5.1 Analysis of Neighborhood Selection Strategy -- 5.2 Performance Evaluation Using Small Instances -- 5.3 Performance Evaluation Using Large Instances -- 6 Conclusion -- References -- An Empirical Analysis of Tabu Lists -- 1 Introduction -- 2 Related Work -- 3 Tabu Search -- 4 Experimental Setup -- 4.1 Tabu Search Implementation -- 4.2 Benchmark Problem -- 4.3 Parameter Tuning.
5 Experimental Analysis -- 5.1 Overall Results -- 5.2 Anytime Behavior -- 5.3 Search Trajectory Networks -- 6 Conclusion and Future Perspectives -- References -- Strategically Influencing Seat Selection in Low-Cost Carriers: A GRASP Approach for Revenue Maximization -- 1 Introduction -- 2 Problem Description -- 3 Proposed Methodology -- 4 Computational Analysis and Results -- 4.1 Case of Study -- 4.2 Numerical Results -- 5 Conclusion -- References -- Behaviour Analysis of Trajectory and Population-Based Metaheuristics on Flexible Assembly Scheduling -- 1 Introduction -- 2 Problem Description -- 3 Related Work -- 4 Meta-heuristics Approaches -- 4.1 Encoding and Decoding -- 4.2 Initialization -- 4.3 Search Operators -- 4.4 Search Strategies -- 5 Experimental Analysis -- 5.1 Problem Sets -- 5.2 Experimental Setup -- 5.3 Results and Discussion -- 6 Conclusions and Further Work -- References -- Matheuristic Variants of DSATUR for the Vertex Coloring Problem -- 1 Introduction -- 2 Problem Statement and State of the Art -- 2.1 Definitions and Notation -- 2.2 Compact ILP Formulations -- 2.3 Standard DSATUR Algorithm -- 3 DSATUR Matheuristic Variants -- 3.1 Initialization -- 3.2 Local Optimization with Larger Neighborhoods -- 3.3 General Algorithm -- 3.4 Dual Bounds -- 4 Computational Results -- 4.1 Experimental Conditions and Methodology -- 4.2 Standard DSATUR with Varied Initialization -- 4.3 DSATUR with Larger Local Optimization -- 4.4 Dual Bounds -- 5 Conclusions and Perspectives -- References -- Combining Neighborhood Search with Path Relinking: A Statistical Evaluation of Path Relinking Mechanisms -- 1 Introduction -- 2 Proposed Metaheuristic Algorithm -- 2.1 Pool of Elite Set Solutions -- 2.2 Neighborhood Search -- 2.3 Path Relinking -- 3 Computational Experiment -- 3.1 Testing Mechanism of Path Relinking -- 3.2 Parameter Setting.
3.3 Computation with XML Instances -- 4 Conclusion -- A Detailed Computational Results -- References -- A General-Purpose Neural Architecture Search Algorithm for Building Deep Neural Networks -- 1 Introduction -- 2 Methodology -- 2.1 Neural Network Modelling -- 2.2 Neural Layers Affinity Indices -- 2.3 General-Purpose Neural Architecture Search -- 3 Results -- 4 Conclusions -- References -- A Dynamic Algorithm Configuration Framework Using Combinatorial Problem Features and Reinforcement Learning -- 1 Introduction -- 2 Methodology -- 2.1 Problem and Test Instances -- 2.2 Metaheuristic Algorithm -- 2.3 Dynamic Configuration Learning -- 3 Implementation and Preliminary Results -- 3.1 LON Investigation -- 3.2 Learning Outcome -- 3.3 Outlook -- References -- Large Neighborhood Search for the Capacitated P-Median Problem -- 1 Introduction -- 2 Mathematical Formulation of the Capacitated P-Median Problem -- 3 Large Neighborhood Search Framework -- 4 LNS for the Capacitated P-Median Problem -- 4.1 Initial Solution -- 4.2 Destroy Operators -- 4.3 Repair Operator -- 4.4 Algorithm Description -- 5 Evaluation -- 5.1 Data Sets -- 5.2 Parameter Configuration -- 5.3 Ablation Analysis --
5.4 Results -- 6 Conclusions -- A Appendix -- References -- Experiences Using Julia for Implementing Multi-objective Evolutionary Algorithms -- 1 Introduction -- 2 The jMetal Framework -- 3 Component-Based Evolutionary Algorithms in Julia -- 4 Performance Evaluation -- 5 Porting jMetal Resources to MetaJul -- 6 Discussion -- 6.1 Research Questions -- 6.2 Further Remarks -- 7 Conclusions -- References -- A Matheuristic Multi-start Algorithm for a Novel Static Repositioning Problem in Public Bike-Sharing Systems -- 1 Introduction -- 2 Literature Review -- 3 Problem Description -- 4 Algorithmic Proposal -- 5 Phase I: Randomized Multi-start Algorithm.
6 Phase II: Optimal Loading Instructions -- 7 Computational Experiments -- 8 Concluding Remarks -- References -- A Disjunctive Graph Solution Representation for the Continuous and Dynamic Berth Allocation Problem -- 1 Introduction -- 2 Problem Overview -- 2.1 Problem Description -- 2.2 Assumptions -- 3 A Disjunctive Graph Representation for the Continuous and Dynamic BAP -- 3.1 A Non-oriented Disjunctive Graph Representation of the Problem -- 3.2 Solution Representation Using an Oriented Disjunctive Graph -- 4 An Iterated Local Search for the Continuous and Dynamic BAP -- 4.1 Initial Solution -- 4.2 Local Search Heuristics -- 4.3 Perturbation -- 4.4 General Framework of the ILS -- 5 Numerical Experiments -- 5.1 Instances Generator -- 5.2 Evaluation of Algorithm ILSdisj -- 6 Conclusion -- References -- Area Coverage in Heterogeneous Multistatic Sonar Networks: A Simulated Annealing Approach -- 1 Introduction -- 2 Problem Description -- 3 Simulated Annealing (SA) -- 3.1 Problem-Specific Components -- 3.2 Algorithm-Specific Components -- 4 Numerical Experiments -- 4.1 Instances -- 4.2 Results -- 4.3 Example of Solution -- 5 Conclusions and Perspectives -- References -- The Use of Metaheuristics in the Evolution of Collaborative Filtering Recommender Systems: A Review -- 1 Introduction -- 2 Background of Recommender Systems -- 3 Collaborative Filtering (CF) Recommendations -- 4 History of Advancements in CF -- 4.1 Neighborhoods and Recommendations -- 4.2 Sparsity and Accurate Neighborhoods -- 4.3 Addressing Sparsity Through Evolutionary Techniques -- 4.4 Addressing Sparsity Through Multi-objective Optimization -- 4.5 Impacts of CF Reliance on Historical Data -- 4.6 Revamping Classical Approaches with Metaheuristics -- 5 Reviews of CF -- 6 Conclusion -- References -- Modelling and Solving a Scheduling Problem with Hazardous Products Dynamic Evolution.
1 Introduction -- 2 Related Works -- 3 Problem Definition -- 4 Iterated Local Search for the RCPSP-RTD -- 5 Computational Experiments -- 5.1 Data Generation -- 5.2 Results Analysis -- 6 Concluding Remarks -- References -- Fixed Set Search Matheuristic Applied to the min-Knapsack Problem with Compactness Constraints and Penalty Values -- 1 Introduction -- 2 Related Literature -- 3 Problem Definition -- 4 A Matheuristic Based on the Fixed Set Search -- 4.1 Generating the Initial Population of Solutions -- 4.2 Fixed Sets -- 4.3 The Use of the Integer Program -- 5 Computational Experiments -- 5.1 Instances -- 5.2 Results -- 6 Conclusions and Future Work -- References -- Improved Golden Sine II in Synergy with Non-monopolized Local Search Strategy -- 1 Introduction -- 2 Related Work -- 2.1 Golden Sine Algorithm II -- 2.2 Non-monopolized Search -- 3 Proposed Approach -- 4 Experimental Results -- 4.1 Friedman Rank Test -- 4.2 Dispersion of the Resulst -- 5 Conclusions and Future Work -- References -- Population of Hyperparametric Solutions for the Design of Metaheuristic Algorithms: An Empirical Analysis of Performance in Particle Swarm Optimization -- 1 Introduction -- 2 Particle Swarm
Optimization -- 3 Hyper Particle Swarm Optimization -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- A GRASP Algorithm for the Meal Delivery Routing Problem -- 1 Introduction -- 2 Related Work -- 3 Problem Description -- 3.1 Users -- 3.2 Apps/Platform -- 3.3 Couriers -- 3.4 Restaurants -- 4 Methodology -- 5 Computational Experiments and Result Analysis -- 5.1 Case of Study -- 5.2 Computational Results -- 6 Conclusions -- References -- Optimization Approaches for a General Class of Single-Machine Scheduling Problems -- 1 Introduction -- 2 Optimization Approach -- 2.1 Optimization Models -- 2.2 Tabu Search -- 3 Preliminary Results -- References.
What Characteristics Define a Good Solution in Social Influence Minimization Problems?.