arXiv subjects

Kuang Bai

Publications and source records attributed to Kuang Bai.

6 recordsLinked to original sources

arXiv2026

Directional first order approach for a class of bilevel programs

In this paper, we study a class of bilevel optimization program, where the feasible set of the lower level program is independent of the upper level variable. For bilevel programs it is known that the first order reformulation of a bilevel program requires the convexity of the lower level program while reformulations involving the value function result in difficult optimization problems. In this paper we propose a directional first order approach which does not require convexity of the lower level program. First, we propose some conditions under which the lower level program can be equivalently characterized by its first order condition over a directional neighborhood around the local optimal condition. Next we give some conditions under which the classical first order optimality condition in the form of M-stationary condition still holds as a necessary optimality condition for the first order reformulation of the bilevel program even when the lower level program is nonconvex.

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arXiv2023

Optimality conditions for bilevel programs via Moreau envelope reformulation

For bilevel programs with a convex lower level program, the classical approach replaces the lower level program with its Karush-Kuhn-Tucker condition and solve the resulting mathematical program with complementarity constraint (MPCC). It is known that when the set of lower level multipliers is not unique, MPCC may not be equivalent to the original bilevel problem, and many MPCC-tailored constraint qualifications do not hold. In this paper, we study bilevel programs where the lower level is generalized convex. Applying the equivalent reformulation via Moreau envelope, we derive new directional optimality conditions. Even in the nondirectional case, the new optimality condition is stronger than the strong stationarity for the corresponding MPCC.

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arXiv2023

Directional derivative of the value function for parametric set-constrained optimization problems

This paper is concerned with the directional derivative of the value function for a very general set-constrained optimization problem under perturbation. Under reasonable assumptions, we obtain upper and lower estimates for the upper and lower Dini directional derivative of the value function respectively, from which we obtain Hadamard directional differentiability of the value function when the set of multipliers is a singleton. Our results do not require convexity of the set involved. Even in the case of a parametric nonlinear program, our results improve the classical ones in that our regularity conditions are weaker and the directional solution set is used which is in general smaller than its nondirectional counterparts.

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arXiv2023

Directional subdifferential of the value function

The directional subdifferential of the value function gives an estimate on how much the optimal value changes under a perturbation in a certain direction. In this paper we derive upper estimates for the directional limiting and singular subdifferential of the value function for a very general parametric optimization problem. We obtain a characterization for the directional Lipschitzness of a locally lower semicontinuous function in terms of the directional subdifferentials. Based on this characterization and the derived upper estimate for the directional singular subdifferential, we are able to obtain a sufficient condition for the directional Lipschitzness of the value function. Finally, we specify these results for various cases when all functions involved are smooth, when the perturbation is additive, when the constraint is independent of the parameter, or when the constraints are equalities and inequalities. Our results extend the corresponding results on the sensitivity of the value function to allow directional perturbations. Even in the case of full perturbations, our results recover or even extend some existing results, including the Danskin's theorem.

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arXiv2020

Directional necessary optimality conditions for bilevel programs

The bilevel program is an optimization problem where the constraint involves solutions to a parametric optimization problem. It is well-known that the value function reformulation provides an equivalent single-level optimization problem but it results in a nonsmooth optimization problem which never satisfies the usual constraint qualification such as the Mangasarian-Fromovitz constraint qualification (MFCQ). In this paper we show that even the first order sufficient condition for metric subregularity (which is in general weaker than MFCQ) fails at each feasible point of the bilevel program. We introduce the concept of directional calmness condition and show that under {the} directional calmness condition, the directional necessary optimality condition holds. {While the directional optimality condition is in general sharper than the non-directional one,} the directional calmness condition is in general weaker than the classical calmness condition and hence is more likely to hold. {We perform the directional sensitivity analysis of the value function and} propose the directional quasi-normality as a sufficient condition for the directional calmness. An example is given to show that the directional quasi-normality condition may hold for the bilevel program.

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arXiv2019

Directional quasi/pseudo-normality as sufficient conditions for metric subregularity

In this paper we study sufficient conditions for metric subregularity of a set-valued map which is the sum of a single-valued continuous map and a locally closed subset. First we derive a sufficient condition for metric subregularity which is weaker than the so-called first-order sufficient condition for metric subregularity (FOSCMS) by adding an extra sequential condition. Then we introduce a directional version of the quasi-normality and the pseudo-normality which is stronger than the new {weak} sufficient condition for metric subregularity but is weaker than the classical quasi-normality and pseudo-normality respectively. Moreover we introduce a nonsmooth version of the second-order sufficient condition for metric subregularity and show that it is a sufficient condition for the new sufficient condition for metric {sub}regularity to hold. An example is used to illustrate that the directional pseduo-normality can be weaker than FOSCMS. For the class of set-valued maps where the single-valued mapping is affine and the abstract set is the union of finitely many convex polyhedral sets, we show that the pseudo-normality and hence the directional pseudo-normality holds automatically at each point of the graph. Finally we apply our results to the complementarity and the Karush-Kuhn-Tucker systems.

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