Approximate Bayesian inference for simulation and optimization (Ilya Ryzhov) -- Optimization for Power Systems and the Smart Grid (Miguel Anjos) -- Semidefinite Approaches for MIQCP: Convex Relaxations and Practical Methods (Hongbo Dong and Nathan Krislock) -- A few strong knapsack facets (Sunil Chopra, Sangho Shim and Daniel E. Steffy) -- On the Performance of SQP Methods for Nonlinear Optimization (Philip E. Gill, Michael A. Saunders and Elizabeth Wong).

This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on August 13-15, 2014. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of deterministic and stochastic optimization techniques in energy, finance, logistics, analytics, healthcare, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.