Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics: Third International Conference, LION 2009 III, . (Lecture Notes in Computer Science, 5851)

ISBN 10: 3642111688 / ISBN 13: 9783642111686

Editore: Springer, 2009

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Dati bibliografici

• Titolo: Learning and Intelligent Optimization: Designing, Implementing and Analyzing Effective Heuristics: Third International Conference, LION 2009 III, . (Lecture Notes in Computer Science, 5851)
• Editore: Springer
• Data di pubblicazione: 2009
• Lingua: Inglese
• ISBN 10: 3642111688
• ISBN 13: 9783642111686
• Rilegatura: Paperback
• Condizione: Like New
• Tipo di libro: book

Descrizione articolo

Riassunto

LION 3, the Third International Conference on Learning and Intelligent Op- mizatioN, was held during January 14 18 in Trento, Italy. The LION series of conferences provides a platform for researchers who are interested in the int- section of e?cient optimization techniques and learning. It is aimed at exploring the boundaries and uncharted territories between machine learning, arti?cial intelligence, mathematical programming and algorithms for hard optimization problems. The considerable interest in the topics covered by LION was re?ected by the overwhelming number of 86 submissions, which almost doubled the 48 subm- sions received for LION s second edition in December 2007. As in the ?rst two editions, the submissions to LION 3 could be in three formats: (a) original novel and unpublished work for publication in the post-conference proceedings, (b) extended abstracts of work-in-progressor a position statement, and (c) recently submitted or published journal articles for oral presentations. The 86 subm- sions received include 72, ten, and four articles for categories (a), (b), and (c), respectively.

Contenuti

Evolutionary Dynamics of Extremal Optimization.- Evolutionary Dynamics of Extremal Optimization.- A Variable Neighborhood Descent Search Algorithm for Delay-Constrained Least-Cost Multicast Routing.- Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks.- New Bounds on the Clique Number of Graphs Based on Spectral Hypergraph Theory.- Beam-ACO Based on Stochastic Sampling: A Case Study on the TSP with Time Windows.- Flexible Stochastic Local Search for Haplotype Inference.- A Knowledge Discovery Approach to Understanding Relationships between Scheduling Problem Structure and Heuristic Performance.- Fitness Landscape Analysis for the Resource Constrained Project Scheduling Problem.- An ACO-Based Reactive Framework for Ant Colony Optimization: First Experiments on Constraint Satisfaction Problems.- Selection of Heuristics for the Job-Shop Scheduling Problem Based on the Prediction of Gaps in Machines.- Position-Guided Tabu Search Algorithm for the Graph Coloring Problem.- Corridor Selection and Fine Tuning for the Corridor Method.- Dynamic Multi-Armed Bandits and Extreme Value-Based Rewards for Adaptive Operator Selection in Evolutionary Algorithms.- Comparison of Coarsening Schemes for Multilevel Graph Partitioning.- Cooperative Strategies and Reactive Search: A Hybrid Model Proposal.- Study of the Influence of the Local Search Method in Memetic Algorithms for Large Scale Continuous Optimization Problems.- MALIOB Workshop Papers.- Neural Network Pairwise Interaction Fields for Protein Model Quality Assessment.- A Graph-Based Semi-supervised Algorithm for Protein Function Prediction from Interaction Maps.- Substitution Matrices and Mutual Information Approaches to Modeling Evolution.