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The Standard Pessimistic Bilevel Problem

L. Lampariello (lorenzo.lampariello***at***uniroma3.it)
S. Sagratella (sagratella***at***diag.uniroma1.it)
O. Stein (stein***at***kit.edu)

Abstract: Pessimistic bilevel optimization problems, as optimistic ones, possess a structure involving three interrelated optimization problems. Moreover, their finite infima are only attained under strong conditions. We address these difficulties within a framework of moderate assumptions and a perturbation approach which allow us to approximate such finite infima arbitrarily well by minimal values of a sequence of solvable single-level problems. To this end, as already done for optimistic problems, for the first time in the literature we introduce the standard version of the pessimistic bilevel problem. For its algorithmic treatment, we reformulate it as a standard optimistic bilevel program with a two follower Nash game in the lower level. The latter lower level game, in turn, is replaced by its Karush-Kuhn-Tucker conditions, resulting in a single-level mathematical program with complementarity constraints. We prove that the perturbed pessimistic bilevel problem, its standard version, the two follower game as well as the mathematical program with complementarity constraints are equivalent with respect to their global minimal points. We study the more intricate connections between their local minimal points in detail. As an illustration, we numerically solve a regulator problem from economics for different values of the perturbation parameters.

Keywords: Pessimistic bilevel programming, standard optimistic bilevel problem, generalized Nash equilibrium problem, mathematical program with complementarity constraints

Category 1: Convex and Nonsmooth Optimization (Nonsmooth Optimization )

Category 2: Nonlinear Optimization (Constrained Nonlinear Optimization )

Category 3: Other Topics (Game Theory )

Citation: Optimization Online, Preprint ID 2018-06-6688, 2018.

Download: [PDF]

Entry Submitted: 06/30/2018
Entry Accepted: 06/30/2018
Entry Last Modified: 06/30/2018

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