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 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.