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January 2017

Seminar: Stochastic reformulations of linear systems and efficient randomized algorithms

January 20, 2017 @ 3:00 pm

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 can be equivalently seen as a stochastic optimization problem, stochastically preconditioned linear system, stochastic fixed point problem and as a probabilistic intersection problem. We propose…

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September 2017

Seminar: Prediction of Stock market crashes,entry exits from bubbles, hedge fund disasters and their prevention

September 25, 2017 @ 2:00 pm - 3:00 pm

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 going up just because people expect them to continue rising. In these cases the prices exceed the fair value based on fundamentals. Jarrow and his…

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October 2017

Seminar: Robust Model Predictive Control

October 27, 2017 @ 4:00 pm - 5:00 pm

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) is an improved MPC form that is robust against the bounded uncertainty. RMPC employs a generalized prediction framework that allows for a meaningful optimization of,…

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November 2017

Seminar: Multi-level Optimization by multi-parametric programming & its use for the solution of Mixed Integer Adjustable Robust Optimization Problems

November 14, 2017 @ 4:00 pm - 5:00 pm

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 programming problems. We are considering bi-level (two decision levels) and tri-level (three decision levels) programming problems. Multi-level programming problems are very challenging to solve even…

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Seminar: Stochastic Vehicle Routing: an Overview and some Recent Advances

November 21, 2017 @ 2:00 pm - 3:00 pm

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 parameters are uncertain at the time where the routes are made have received significantly less attention, in spite of the fact that there are many…

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January 2018

Seminar: ADMM and Random Walks on Graphs

January 19 @ 11:15 am - 12:30 pm

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 by a graph G. This was followed by a conjecture that ADMM is faster than gradient descent by a square root factor in its convergence…

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April 2018

Seminar: Large neighbourhood Benders’ search

April 17 @ 2:00 pm - 3:30 pm

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 in bespoke Benders' decomposition implementations. To date, only ad hoc approaches have been developed to enhance the Benders' decomposition algorithm using large neighbourhood search techniques---namely…

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Seminar: Computing Pessimistic Leader-Follower Equilibria with Multiple Followers

April 25 @ 2:00 pm - 3:00 pm

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 Nash Equilibrium. We consider two natural cases, the optimistic one where the followers select a Nash Equilibrium maximizing the leader's utility and the pessimistic one…

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May 2018

Seminar: More Virtuous Smoothing and Embracing the Ghost of Rolle

May 25 @ 2:00 pm - 3:00 pm

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 behaved derivative at 0 (for example, root functions). Extending earlier work of Lee and Skipper, we give general conditions under which our smoothing is concave…

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October 2018

Seminar: Random projections in mathematical programming

October 3 @ 3:00 pm - 4:00 pm

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 form of approximation guarantee is usually preferable. In this talk we shall discuss a set of approximating reformulations to various classes of mathematical programming problems…

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