Title: Solution of an old problem in vector optimisation - Support function of the generalised Jacobian Speaker: Prof. Abbas Edalat Affiliation: Department of Computing - Imperial College Location: Room 217 Huxley Building Time: 3:00pm (1 hour) Abstract. Many optimisation problems are non-smooth in the sense that the objective function is not differentiable. This is invariably the case in many... Read more »

Title: On Bit Representations of Mixed-Integer Quadratic Programs. Speaker: Prof. Adam Letchford Affiliation: Management School - Lancaster University Location: Room 217 Huxley Building Time: 3:00pm (1 hour) Abstract. A standard trick in integer programming is to replace each bounded general-integer variable with a small number of binary variables, using the bit representation of the given variable.... Read more »

Title: Smart Grids and Optimization - A Winning Combination Speaker: Prof. Miguel Anjos Affiliation: Polytechnique Montreal Location: Room 217 Huxley Building Time: 1:30pm (1 hour) Abstract. A smart grid is the combination of a traditional electrical power system with information and energy both flowing back and forth between suppliers and consumers. This new paradigm introduces major... Read more »

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 »