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Approximating Security Values of MinSup Problems with Quasi-variational Inequality Constraints

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We consider a two-stage model where a leader, according to its risk-averse proneness, solves a MinSup problem with constraints corresponding to the reaction sets of a follower and defined by the solutions of a quasi-variational inequality (i.e. a variational inequality having constraint sets depending on its own solutions) which appear in concrete economic models such as social and economic networks, financial derivative models, transportation network congestion and traffic equilibrium. In general the infimal value of a MinSup (or the maximal value of a MaxInf) problem with quasi-variational inequality constraints is not stable under perturbations in the sense that the sequence of optimal values for the perturbed problems may not converge to the optimal value of the original problem even in presence of nice data. Thus, we introduce different types of approximate values for this problem, we investigate their asymptotical behavior under perturbations and we emphasized the results concerning MinSup problems with variational inequality constraints as well results holding under stronger assumptions that can be more easily employed in applications.

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  • M. Beatrice Lignola & Jacqueline Morgan, 2012. "Approximating Security Values of MinSup Problems with Quasi-variational Inequality Constraints," CSEF Working Papers 321, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy, revised 09 Oct 2014.
    • Handle: RePEc:sef:csefwp:321
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    1. M. Beatrice Lignola & Jacqueline Morgan, 2015. "MinSup Problems with Quasi-equilibrium Constraints and Viscosity Solutions," CSEF Working Papers 393, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    2. M. Beatrice Lignola & Jacqueline Morgan, 2017. "Inner Regularizations and Viscosity Solutions for Pessimistic Bilevel Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 173(1), pages 183-202, April.
    3. Bo Zeng, 2020. "A Practical Scheme to Compute the Pessimistic Bilevel Optimization Problem," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1128-1142, October.

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