Learning and Intelligent Optimization

Inhaltsverzeichnis

• 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.