Learning and Intelligent Optimization - 19th International Conference, LION 19, Prague, Czech Republic, June 15-19, 2025, Proceedings, Part II

The two-volume set LNCS 15744 + 15745 constitutes the proceedings of the 19th International Conference on Learning and Intelligent Optimization, LION 2025, which was held in Prague, Czech Republic, during June 15 19, 2025.
The 40 full papers included in the proceedings were carefully reviewed and selected from 70 submissions. They focus on exploring the intersections of Artificial Intelligence, Machine Learning, and Operations Research.

Inhaltsverzeichnis

.- Autoregressive RL Approach for Mixed-Integer Linear Programs.
.- Algorithm Configuration in the Unified Planning Framework.
.- Learning to Repair Infeasible$^*$ Problems with Deep Reinforcement Learning on Graphs.
.- Optimal Matched Block Design For Multi-Arm Experiments.
.- CHORUS: Zero-shot Hierarchical Retrieval and Orchestration for Generating Linear Programming Code.
.- Taxi re-positioning considering driver compliance.
.- A Shared Memory Optimal Parallel Redistribution Algorithm for SMC Samplers with Variable Size Samples.
.- A Hybrid Quantum-Inspired and Deep Learning Approach for the Capacitated Vehicle Routing Problem with Time Windows.

Zusammenfassung

The two-volume set LNCS 15744 + 15745 constitutes the proceedings of the 19th International Conference on Learning and Intelligent Optimization, LION 2025, which was held in Prague, Czech Republic, during June 15–19, 2025.
The 40 full papers included in the proceedings were carefully reviewed and selected from 70 submissions. They focus on exploring the intersections of Artificial Intelligence, Machine Learning, and Operations Research.

Produktdetails

• Mitarbeit: Milan Hladik (Herausgeber), Hossein Moosaei (Herausgeber), Yingqian Zhang (Herausgeber)
• Verlag: Springer, Berlin
• Sprache: Englisch
• Produktform: Taschenbuch
• Erscheint: 03.12.2025
• EAN: 9783032091918
• ISBN: 978-3-0-3209191-8
• Seiten: 298
• Illustration: XI, 298 p. 76 illus.
• Serie: Lecture Notes in Computer Science
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Mathematik > Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Operations Research, Künstliche Intelligenz, machine learning, Algorithms, Optimization, Artificial Intelligence, Deep Learning, Wahrscheinlichkeitsrechnung und Statistik, Informationstechnik (IT), allgemeine Themen, Theoretische Informatik, Mathematik für Informatiker, Reinforcement Learning, Theory of Computation, Numerical analysis, Probability and Statistics in Computer Science, Computing Milieux, Computer Application in Social and Behavioral Sciences, Intelligent Systems, mathematical programming, metaheuristics, search methodologies