Title: Multi-level Optimization by multi-parametric programming & its use for the solution of Mixed Integer Adjustable Robust Optimization Problems Speaker: Prof. Michel Gendreau Affiliation: Dept. of Mathematics and Industrial Engineering, Polytechnique Montréal Location: LG19a, Business School Time: 2:00pm Abstract. While Vehicle Routing Problems have now been studied extensively for more than 50 years, those in which some... Read more »

Title: ADMM and Random Walks on Graphs Speaker: Prof. José Bento Affiliation: Dept. of Computer Science, Boston College Location: Room 217 Huxley Building Time: 11:15am - 12:30pm Abstract. A connection between the distributed alternating direction method of multipliers (ADMM) and lifted Markov chains was recently proposed by Franca et al. 2016 for a non-strictly-convex consensus problem parametrized... Read more »

Title: Large neighbourhood Benders' search Speaker: Dr. Stephen Maher Affiliation: Lancaster University Management School Location: Room 218 Huxley Building Time: 14:00 - 15:30 Abstract. Enhancements for the Benders' decomposition algorithm can be derived from large neighbourhood search (LNS) heuristics. While mixed-integer programming (MIP) solvers are endowed with an array of LNS heuristics, their use is typically limited... Read more »

Title: Computing Pessimistic Leader-Follower Equilibria with Multiple Followers Speaker: Dr Stefano Coniglio Affiliation: Dept. of Mathematical Sciences, Southampton University Location: Room 217 Huxley Building Time: 14:00 - 15:00 Abstract. We investigate the problem of computing a Leader-Follower equilibrium in Stackelberg games where two or more followers react to the strategy chosen by the (single) leader by playing a... Read more »

Title: More Virtuous Smoothing and Embracing the Ghost of Rolle Speaker: Prof Jon Lee Affiliation: Industrial and Operations Engineering, College of Engineering, University of Michigan Location: LT 308 Huxley Building Time: 14:00 - 15:00 Abstract. In the context of global optimization of mixed-integer nonlinear optimization formulations, we consider smoothing univariate concave increasing functions that have poorly... Read more »

Title: Random projections in mathematical programming Speaker: Dr Leo Liberti Affiliation: CNRS LIX, École Polytechnique Location: 218 Huxley Building Time: 15:00 - 16:00 Abstract. In the algorithmic trade-off between generality and efficiency, sometimes the only way out is to accept approximate methods. If all else fails, we can always fall back on heuristic methods. But some... Read more »

Title: Arrangements of Circles and Spheres leading to Convex Hulls with Minimal Boundaries Speaker: Dr Josef Kallrath Affiliation: Advanced Business Analytics, BASF SE, Germany Location: 218 Huxley Building Time: 15:00 - 16:00 Abstract. We present and solve a new computational geometry optimization problem in 2D and 3D and provide theoretical insights. Circles (2D) and Spheres (3D)... Read more »

Title: Capacity upper bounds for deletion-type channels Speaker: Dr Mahdi Cheraghchi Affiliation: Dept of Computing, Imperial College London Location: 218 Huxley Building Time: 16:00 - 17:00 Abstract. We develop a systematic approach, based on convex programming and real analysis, for obtaining upper bounds on the capacity of the binary deletion channel and, more generally, channels with... Read more »

Title: Model-based design of optimal experiments using exact confidence regions Speaker: Dr Radoslav Paulen Affiliation: Institute of Information Engineering, Automation and Mathematics, Slovak University of Technology Location: 218 Huxley Building Time: 16:00 - 17:00 Abstract. This talk discusses a model-based optimal experiment design (OED) for nonlinear systems. OED represents a methodology for optimizing the geometry of... Read more »

Title: Generalized maximum entropy estimation Speaker: Dr David Sutter Affiliation: Institute for Theoretical Physics, ETH Zurich Location: 217 Huxley Building Time: 14:00 - 15:00 Abstract. We consider the problem of estimating a probability distribution that maximizes the entropy while satisfying a finite number of moment constraints, possibly corrupted by noise. Based on duality of convex programming,... Read more »