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A computation strategy for a two-stage stochastic equilibrium problem

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A computation strategy for a two-stage stochastic equilibrium problem
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Herausgeber
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Abstract
In this talk, we present a problem of strategic planning for capacity investment and production under uncertainty, in a competitive market. We model it as a general equilibrium problem, i.e., a collection of multi-agent optimization problems with an equilibrium constraint (supply meets demand), and we propose a solution method based on a scheme that considers: i) a stagewise-decomposition procedure using Progressive Hedging, ii) a representative agent representation, and iii) a decomposition-type method for its solution, such as the Alternating Direction Method of Multipliers (ADMM). We illustrate the numerical performance of the algorithm by solving a stochastic infrastructure planning problem for the electric vehicule fast-charging station problem over a small network.