“…Apart from the applications of the two stage SEPEC models discussed in this section, there are some potential applications in transportation and economics [15,21,13,28], internet service problems [36] and airline revenue management problems [16].…”
Section: Oligopolistic Transit Marketmentioning
confidence: 99%
“…The concept of stationary points are important in optimization as it provides some information of optimality. This is particularly so in MPECs where obtaining a global optimal solution is often difficult and consequently various of stationary points are investigated [13,44]. The concept of Nash stationary point is relatively new: it was introduced by Hu and Ralph [15].…”
Section: Nash Stationary Pointsmentioning
confidence: 99%
“…Zhang, Xu and Wu [44] developed a two stage SEPEC model to study generator's competition in electricity forward and spot markets and their interactions. Henrion and Römisch [13] proposed a two stage SEPEC model for studying competition in electricity markets. The authors investigated M-stationary points of the SEPEC model under the condition that the market demand in the spot market has a finite distribution.…”
This paper presents a two stage stochastic equilibrium problem with equilibrium constraints (SEPEC) model. Some source problems which motivate the model are discussed. Monte Carlo sampling method is applied to solve the SEPEC. The convergence analysis on the statistical estimators of Nash equilibria and Nash stationary points are presented.
“…Apart from the applications of the two stage SEPEC models discussed in this section, there are some potential applications in transportation and economics [15,21,13,28], internet service problems [36] and airline revenue management problems [16].…”
Section: Oligopolistic Transit Marketmentioning
confidence: 99%
“…The concept of stationary points are important in optimization as it provides some information of optimality. This is particularly so in MPECs where obtaining a global optimal solution is often difficult and consequently various of stationary points are investigated [13,44]. The concept of Nash stationary point is relatively new: it was introduced by Hu and Ralph [15].…”
Section: Nash Stationary Pointsmentioning
confidence: 99%
“…Zhang, Xu and Wu [44] developed a two stage SEPEC model to study generator's competition in electricity forward and spot markets and their interactions. Henrion and Römisch [13] proposed a two stage SEPEC model for studying competition in electricity markets. The authors investigated M-stationary points of the SEPEC model under the condition that the market demand in the spot market has a finite distribution.…”
This paper presents a two stage stochastic equilibrium problem with equilibrium constraints (SEPEC) model. Some source problems which motivate the model are discussed. Monte Carlo sampling method is applied to solve the SEPEC. The convergence analysis on the statistical estimators of Nash equilibria and Nash stationary points are presented.
“…In order to apply Proposition 3.2, we have to compute explicitly the partial second-order subdifferential ∂ 2 x Ψ (explicit formulae for the other term D * N X are available from the literature, see, e.g., [5]). As a first step, we reduce the computation of ∂ 2…”
Section: Basic Concepts and Notationmentioning
confidence: 99%
“…The assumption of strict complementarity yields that v * ∈ Ker D I and u * ∈ Im D I , where D I is the reduction of D to its active rows (see, e.g., [5,Corollary 3.7]). This entails that u * , v * = 0 which may be exploited in order to reduce the first equation in (25) to…”
Section: Application To Conditioning In the Case Of Simple Recoursementioning
In this paper a condition number for linear-quadratic two-stage stochastic optimization problems is introduced as the Lipschitz modulus of the multifunction assigning to a (discrete) probability distribution the solution set of the problem. Being the outer norm of the Mordukhovich coderivative of this multifunction, the condition number can be estimated from above explicitly in terms of the problem data by applying appropriate calculus rules. Here, a chain rule for the extended partial second-order subdifferential recently proved by Mordukhovich and Rockafellar plays a crucial role. The obtained results are illustrated for the example of two-stage stochastic optimization problems with simple recourse.
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