3 présentations

• 
  10h30 - 10h55

  Hub interdiction problem: Alternate solution approaches

  • Sachin Jayaswal, prés., Indian Institute of Management Ahmedabad
  • Prasanna Ramamoorthy, Indian Institute of Management Ahmedabad
  • Navneet Vidyarthi, Concordia University
  • Ankur Sinha, Indian Institute of Management Ahmedabad

  We study the hub interdiction problem. The problem is modeled as a 2-stage sequential game, resulting in a bi-level mixed integer program. We present alternate approaches to reduce the model to single level, followed by efficient exact methods to solve the problem to optimality.

• 
  10h55 - 11h20

  Optimal policy for reforming energy subsidies in presence of heterogeneous consumers and suppliers

  • Hossein Mirzapour, prés., HEC Montréal
  • Michèle Breton, GERAD, HEC Montréal

  To raise the necessary public support for the energy consumption subsidies reform, a prevalent recommendation is to redistribute its revenue among the affected consumers. However, the main challenge to design a feasible and optimal policy is the scale and target of compensation payments, particularly in the presence of heterogeneous consumers and suppliers of non-energy goods. We study the problem of a social planner, which aims to maximize the national gain of reform while expecting a minimum purchasing power for the households. We analyze the impact of heterogeneity on the feasibility range of such a reform and compare the result of different compensation policies.

• 
  11h20 - 11h45

  Unit commitment under market equilibrium constraints

  • Bernard Fortz, prés., Université Libre de Bruxelles
  • Luce Brotcorne, INRIA Lille
  • Fabio D'Andreagiovanni, Heudiasyc, UTC
  • Jérôme De Boeck, Université Libre de Bruxelles

  We consider an extension of the Unit Commitment problem with a second level of decisions ensuring that the produced quantities are cleared at market equilibrium. In their simplest form, market equilibrium constraints are equivalent to the first-order optimality conditions of a linear program. The UC in contrast is usually a mixed-integer nonlinear program (MINLP), that is linearized and solved with traditional Mixed Integer (linear) Programming (MIP) solvers. Taking a similar approach, we are faced to a bilevel optimization problem where the first level is a MIP and the second level linear.