Modeling, Simulation and Optimization for Science and Technology

Foreword.- 1. A Unified Approach to Measuring Accuracy of Error Indicators, by Immanuel Anjam, Olli Mali, Pekka Neittaanmäki, and Sergey Repin.- 2. On the Numerical Solution of the Dirichlet Problem for the Elliptic (s2) Equation, by Alexandre Caboussat.- 3. Multiple-Gradient Descent Algorithm (MGDA) for Pareto-Front Identification, by Jean-Antoine Désidéri4. On Alternating Direction Methods of Multipliers: A Historical Perspective, by Roland Glowinski.- 5. Numerical Analysis and Simulation of the Dynamics of Mountain Glaciers, by Guillaume Jouvet and Jacques Rappaz.- 6. Fast Nash Hybridized Evolutionary Algorithms for Single and Multi-Objective Design Optimization in Engineering, by Dong Seop Lee, Jacques Periaux, and Sung Wook Lee.- 7. An Augmented Lagrangian Method for the Microstructure of a Liquid Crystal Model, by Ping Lin and Xue-Cheng Tai.- 8. On an Extension of the First Korn Inequality to Incompatible Tensor Fields on Domains of Arbitrary Dimensions, by Patrizio Neff, Dirk Pauly and Karl-Josef Witsch.- 9. A Guide for the Selecting of a Numerical Methodology Adapted to the Analysis of Extreme Events, by Pierre C. Perrier.- 10. Optimization Under Uncertainty Using the Generalized Inverse Distribution Function, by Domenico Quagliarella, Giovanni Petrone and Gianluca Iaccarino.- 11. Automating the Parameter Selection in VRP: an Off-line Parameter Tuning Tool Comparison, by Jussi Rasku, Nysret Musliu, and Tommi Kärkkäinen.- 12. Comparison of Local Computational Approaches for Unsteady Viscous Incompressible Flows, by Nobuyuki Satofuka, Koji Morinishi, Itaru Tanno, Tomohisa Hashimoto, Takahiro Yasuda, and Yoshihiro Tanaka.- 13. Parameter Rating by Diffusion Gradient, by Guy Wolf, Amir Averbuch, and Pekka Neittaanmäki.