Learning and Intelligent Optimization
Springer International Publishing (Verlag)
978-3-031-75622-1 (ISBN)
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This book constitutes the refereed proceedings of the 18th International Conference on Learning and Intelligent Optimization, LION 18, held in Ischia Island, Italy, in June 2024.
The 31 full papers and 4 short papers presented in these proceedings were carefully reviewed and selected from 58 submissions. These papers focus on the current research, challenges and applications in the fields of Artificial Intelligent, Machine Learning and Operations Research.
Randomized Greedy Sampling for JSSP.- Binarized Monte Carlo Search for Selection Problems.- Effective Kinodynamic Planning and Exploration through Quality Diversity and Trajectory Optimization.- Decoupled Design of Experiments for Expensive Multi objective Problems.- C2VRPTW Assigning capacity to vehicles and nodes in a Vehicle Routing Problem for real-world delivery application.- A constrained JKO scheme for effective and efficient Wasserstein Gradient Flows.- MLE free Gaussian Process based Bayesian Optimization.- Efficient vertex linear orderings to find minimal Feedback Arc Sets (minFAS).- A Real Time Adaptive Tabu Search for Handling Zoom In/Out in Map Labeling Problem.- An SMC Sampler for Decision Trees with Enhanced Initial Proposal for Stochastic Metaheuristic Optimization.- Multi Assignment Schedule A New Behavioral Cloning Method for the Job Shop Scheduling Problem.- An imitation based learning approach using DAgger for the Casual Employee Call Timing Problem.- Conditional Importance Resampling for an Enhanced Sequential Monte Carlo Sampler.- Applying Instance Space Analysis to Optimize the Construction of Matheuristics.- WANCE Learnt Clause Evaluation Method for SAT Solver Using Graph Structure.- Multi output regression for travel demand estimation in an urban road network.- Approximate dynamic programming for inland empty container inventory management.- Algorithm Switching for Multiobjective Predictions in Renewable Energy Markets.- ClassBO Bayesian Optimization for Heterogeneous Functions.- How evolutionary algorithms consume energy depending on the language and its level.- CLS Luigi Analytics Pipeline Synthesis.- A R2 based Multi objective Reinforcement Learning Algorithm.- Robust Airline Fleet and Crew Scheduling: A Matheuristic Approach.- Measuring Social Mood on Economy During Covid Times A BiLSTM Neural Network Approach.- Deep Learning for the Classification of Ports in Maritime Transport Statistics via AIS Data.- Multi objective Stochastic Optimization with AI Predictions on Management of Battery Energy Storage Systems.- Efficient Line Search Method Based on Regression and Uncertainty Quantification.- Parallelizing High Dimensional Surrogate Based Discrete Multi Objective Optimization with Constrain.- A Bayesian approach for prompt optimization in LLMs.- Synergies of Deep and Classical Exploratory Landscape Features for Automated Algorithm Selection.- Sustainable Development Index using MILP to assign relative weight to different UNSDG parameters.- An Evaluation of Domain agnostic Representations to Enable Multi task Learning in Combinatorial Optimisation.- Heuristic algorithms for the planar intermodal p hub location a possibilistic clustering approach.- Machine Learning Optimized Orthogonal Basis Piecewise Polynomial Approximation.- An Approximate and Optimize Method for Security Constrained AC Optimal Power Flow.- auto sktime Automated Time Series Forecasting.
Erscheint lt. Verlag | 12.2.2025 |
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Reihe/Serie | Lecture Notes in Computer Science |
Zusatzinfo | XIII, 466 p. 118 illus. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Mathematik / Informatik ► Mathematik ► Analysis |
Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
Schlagworte | Artificial Intelligence • Deep learning • Heuristics • machine learning • Mathematical Programming • Metaheuristics • Optimization |
ISBN-10 | 3-031-75622-3 / 3031756223 |
ISBN-13 | 978-3-031-75622-1 / 9783031756221 |
Zustand | Neuware |
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