Title: Stochastic reformulations of linear systems and efficient randomized algorithms Speaker: Dr. Peter Richtarik Affiliation: School of Mathematics, University of Edinburgh Location: Room 217 Huxley Building Time: 3:00pm Abstract. We propose a new paradigm for solving linear systems. In our paradigm, the system is reformulated into a stochastic problem, and then solved with a randomized algorithm. Our reformulation... Read more »

Title: Prediction of Stock market crashes,entry exits from bubbles, hedge fund disasters and their prevention Speaker: Prof. William T. Ziemba Affiliation: Sauder School of Business, University of British Columbia Location: LG19b Seminar Room, Business School Time: 2:00pm Abstract. Bubbles occur in financial markets from time to time. By a bubble we mean that the prices are... Read more »

Title: Robust Model Predictive Control Speaker: Dr. Saša V. Raković Location: Room 218 Huxley Building Time: 4:00pm Abstract.  Model predictive control (MPC) is an advanced control technique that employs an open–loop online optimization in order to take account of system dynamics, constraints and control objectives and to obtain the best current control action. Robust MPC (RMPC)... Read more »

Title: Multi-level Optimization by multi-parametric programming & its use for the solution of Mixed Integer Adjustable Robust Optimization Problems Speaker: Prof. Stratos Pistikopoulos, FREng Affiliation: Artie McFerrin Department of Chemical Engineering, Texas A&M University Location: Room 217 Huxley Building Time: 4:00pm Abstract. Optimization problems involving multiple decision makers at different decision levels are referred to as multi-level... Read more »

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 »