Optimization and Learning

7th International Conference, OLA 2024, Dubrovnik, Croatia, May 13-15, 2024, Revised Selected Papers
Erscheinungsjahr 2025
ISBN: 978-3-031-77940-4
Verlag: Springer Nature Switzerland

Buch, Englisch, Band 2311, 322 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 511 g

Reihe: Communications in Computer and Information Science

This book constitutes the refereed proceedings of the 7th International Conference on Optimization and Learning, OLA 2024, held in Dubrovnik, Croatia, during May 13–15, 2024.

The 24 full papers presented here were carefully reviewed and selected from 64 submissions. They were organized in the following topical sections: synergies between optimization and machine learning; enhancing optimization and learning techniques; transportation and routing; and applications.

Zielgruppe

Research

Autoren/Hrsg.

Dorronsoro, Bernabé

Talbi, El-Ghazali

Zagar, Martin

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker

Inhaltsverzeichnis

.- Synergies Between Optimization and Machine Learning.
.- How is the objective function of the Feature Selection problem formulated?.
.- HOTS : A containers resource allocation hybrid method using machine.
.- Optimisation-based classi?cation tree: A game theoretic approach to group fairness.
.- JaxDecompiler: Rede?ning Gradient-Informed Software Design.
.- Adapted Q-learning for the Blocking Job Shop Scheduling Problem.
.- NeuroLGP-SM: A Surrogate-assisted Neuroevolution Approach using Linear Genetic Programming.
.- Neural Architecture Tuning: A BO-Powered NAS Tool.
.- Enhancing Optimization and Learning Techniques.
.- A Multi-objective Clustering Algorithm Integrating Intra-clustering and Inter-clustering Measures.
.- A Bayesian Optimization Approach to Algorithm Parameter Tuning in Constrained Multiobjective Optimization.
.- Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning.
.- A Benchmark for Missing Data Imputation Techniques: development perspectives and performance comparative.
.- Approaching Single-Episode Survival Reinforcement Learning with Safety-Threshold Q-Learning.
.- Feature Selection Based on Membrane Clustering.
.- Transportation and Routing.
.- Learning Insertion Patterns to Enhance Operational E?ciency in Large-Scale Dial-a-Ride Systems
.- A Constraint Programming Approach for the Preference Tourist Trip Design Problem.
.- Solving a shareable-setup time prize collection VRP applied to an electrical maintenance sector.
.- Applications.
.- Biologically-Inspired Algorithms for Adaptive Non-Player Character Behavior in Video-Games.
.- Optimization of Hydro Generation and Load Forecasting Based On LSTN.
.- Patient Visits Forecasting in the Post-Pandemic Era at Emergency Departments.
.- Nature-Inspired Techniques for Combinatorial Reverse Auctions in Electricity Consumption.
.- Robust Models for Learning Languages.
.- Advancing Road Safety Metrics: Exploring Index construction.
.- S3EA: A Self-Supervised Stacked Ensemble Framework for Robust Anomaly Detection to Reduce  False Alarms.
.- A Parallel Genetic Algorithm for Qubit Mapping on Noisy Intermediate-Scale Quantum Machines.