Learning and Intelligent Optimization

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 for Rich Vehicle Routing Problems.- Optimized Ensembles for Clustering Noisy Data.- Stochastic Local Search for the Optimization of Secondary Structure Packing in Proteins.- Systematic Improvementof