Risk-neutral PDE-constrained generalized Nash equilibrium problems
研究一类风险中性的广义纳什均衡问题，其中每个玩家的可行策略受随机输入的线性椭圆偏微分方程约束，并推导了均衡存在性和最优性条件，提出了基于Moreau-Yosida近似的松弛算法。
Abstract A class of risk-neutral generalized Nash equilibrium problems is introduced in which the feasible strategy set of each player is subject to a common linear elliptic partial differential equation with random inputs. In addition, each player’s actions are taken from a bounded, closed, and convex set on the individual strategies and a bound constraint on the common state variable. Existence of Nash equilibria and first-order optimality conditions are derived by exploiting higher integrability and regularity of the random field state variables and a specially tailored constraint qualification for GNEPs with the assumed structure. A relaxation scheme based on the Moreau-Yosida approximation of the bound constraint is proposed, which ultimately leads to numerical algorithms for the individual player problems as well as the GNEP as a whole. The relaxation scheme is related to probability constraints and the viability of the proposed numerical algorithms are demonstrated via several examples.