2018 Optimization Days

HEC Montréal, Québec, Canada, May 7 — 9, 2018

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MA11 Game theory

May 7, 2018 10:30 AM – 12:10 PM

Location: Xerox Canada (48)

Chaired by Bernard Fortz

3 Presentations

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    10:30 AM - 10:55 AM

    Hub interdiction problem: Alternate solution approaches

    • Sachin Jayaswal, presenter, 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.

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    10:55 AM - 11:20 AM

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

    • Hossein Mirzapour, presenter, 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.

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    11:20 AM - 11:45 AM

    Unit commitment under market equilibrium constraints

    • Bernard Fortz, presenter, 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.

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