4 présentations

• 
  10h30 - 10h55

  A Bayesian Approach to the Exploration/Exploitation Dilemma

  • Ilya Ryzhov, prés., Princeton University
  • Warren Powell, Princeton University

  We use a correlated Bayesian belief model to represent our uncertainty about the value function in ADP. Correlations between the values of different states allow us to learn about multiple states from a single decision. We apply the knowledge gradient concept from optimal learning to create a new exploration strategy.

• 
  10h55 - 11h20

  Optimal Control of a Two Dam Hydroelectric Facility Under Time Varying Prices

  • Matt Davison, prés., Departments of Applied Mathematics and Statistical & Actuarial Sciences, Richard Ivey School of Business, The University of Western Ontario

  We investigate optimal control strategies for the variable price electricity market operations of a hydro-electric facility comprising two dams linked in series by a common reservoir which receives the outflow from the first dam and supplies the inflow to the second dam. Using a dynamic programming approach, we are able to obtain some interesting insights about the behaviour of these plants and compare the similarities and differences of the pump-wait-release cycle of this two dam system to a similar one dam system. In particular, we show that the electricity price plays a more important role in a two dam system than in a one dam system.

• 
  11h20 - 11h45

  Extending the Simulations and Regressions A.D.P. Approach to Value and Control a Hydropower System

  • Michel Denault, prés., GERAD - HEC Montréal
  • Mathieu Rousseau, KPMG
  • Jean-Guy Simonato, HEC Montréal
  • Lars Stentoft, HEC Montréal

  We solve a control problem by using simulations and regressions, a common approach in approximate dynamic programming. Specifically, in a hydropower system problem, we have one exogeneous stochastic state variable, power price, and one endogeneous state variable, the water level in the dam. Neither is discretized.

• 
  11h45 - 12h10

  The Optimization Strategy of the Model-Based Analysis of Cell Divisions in Arabidopsis Leaf

  • Leila Kheibarshekan, prés., Ghent University

  We studied the temporal control of epidermal cell divisions in the Arabidopsis leaf. We built a mathematical model with several parameters to study the rules whereby different cell types divide and expand. To optimize the parameters, the experimental data were fitted into a computational model by the downhill simplex method or Nelder-Mead method.