Learning and Intelligent Optimization
Springer Berlin (Verlag)
978-3-642-13799-0 (ISBN)
Main Track (Regular Papers).- A Column Generation Heuristic for the General Vehicle Routing Problem.- A Combination of Evolutionary Algorithm, Mathematical Programming, and a New Local Search Procedure for the Just-In-Time Job-Shop Scheduling Problem.- A Math-Heuristic Algorithm for the DNA Sequencing Problem.- A Randomized Iterated Greedy Algorithm for the Founder Sequence Reconstruction Problem.- Adaptive "Anytime" Two-Phase Local Search.- Adaptive Filter SQP.- Algorithm Selection as a Bandit Problem with Unbounded Losses.- Bandit-Based Estimation of Distribution Algorithms for Noisy Optimization: Rigorous Runtime Analysis.- Consistency Modifications for Automatically Tuned Monte-Carlo Tree Search.- Distance Functions, Clustering Algorithms and Microarray Data Analysis.- Gaussian Process Assisted Particle Swarm Optimization.- Learning of Highly-Filtered Data Manifold Using Spectral Methods.- Multiclass Visual Classifier Based on Bipartite Graph Representation of Decision Tables.- Main Track (Short Papers).- A Linear Approximation of the Value Function of an Approximate Dynamic Programming Approach for the Ship Scheduling Problem.- A Multilevel Scheme with Adaptive Memory Strategy for Multiway Graph Partitioning.- A Network Approach for Restructuring the Korean Freight Railway Considering Customer Behavior.- A Parallel Multi-Objective Evolutionary Algorithm for Phylogenetic Inference.- Convergence of Probability Collectives with Adaptive Choice of Temperature Parameters.- Generative Topographic Mapping for Dimension Reduction in Engineering Design.- Learning Decision Trees for the Analysis of Optimization Heuristics.- On the Coordination of Multidisciplinary Design Optimization Using Expert Systems.- On the Potentials of Parallelizing Large Neighbourhood Search forRich Vehicle Routing Problems.- Optimized Ensembles for Clustering Noisy Data.- Stochastic Local Search for the Optimization of Secondary Structure Packing in Proteins.- Systematic Improvement of Monte-Carlo Tree Search with Self-generated Neural-Networks Controllers.- Special Session: LION-SWOP.- Grapheur: A Software Architecture for Reactive and Interactive Optimization.- The EvA2 Optimization Framework.- Special Session: LION-CCEC.- Feature Extraction from Optimization Data via DataModeler's Ensemble Symbolic Regression.- Special Session: LION-PP.- Understanding TSP Difficulty by Learning from Evolved Instances.- Time-Bounded Sequential Parameter Optimization.- Pitfalls in Instance Generation for Udine Timetabling.- Special Session: LION-MOME.- A Study of the Parallelization of the Multi-Objective Metaheuristic MOEA/D.- An Interactive Evolutionary Multi-objective Optimization Method Based on Polyhedral Cones.- On the Distribution of EMOA Hypervolumes.- Adapting to a Realistic Decision Maker: Experiments towards a Reactive Multi-objective Optimizer.
Erscheint lt. Verlag | 7.7.2010 |
---|---|
Reihe/Serie | Lecture Notes in Computer Science | Theoretical Computer Science and General Issues |
Zusatzinfo | XIV, 344 p. 97 illus. |
Verlagsort | Berlin |
Sprache | englisch |
Themenwelt | Informatik ► Theorie / Studium ► Algorithmen |
Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
Schlagworte | Algorithm analysis and problem complexity • algorithms • evolutionary algorithm • evolutionary algorithms • Heuristic Search • learning • Metaheuristic • Optimization • particle swarm • Runtime Analysis • Software engineering |
ISBN-10 | 3-642-13799-7 / 3642137997 |
ISBN-13 | 978-3-642-13799-0 / 9783642137990 |
Zustand | Neuware |
Haben Sie eine Frage zum Produkt? |
aus dem Bereich