Inexact direct-search methods for bilevel optimization problems

IF 1.6 2区 数学 Q2 MATHEMATICS, APPLIED Computational Optimization and Applications Pub Date : 2024-03-21 DOI:10.1007/s10589-024-00567-7
Youssef Diouane, Vyacheslav Kungurtsev, Francesco Rinaldi, Damiano Zeffiro
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Abstract

In this work, we introduce new direct-search schemes for the solution of bilevel optimization (BO) problems. Our methods rely on a fixed accuracy blackbox oracle for the lower-level problem, and deal both with smooth and potentially nonsmooth true objectives. We thus analyze for the first time in the literature direct-search schemes in these settings, giving convergence guarantees to approximate stationary points, as well as complexity bounds in the smooth case. We also propose the first adaptation of mesh adaptive direct-search schemes for BO. Some preliminary numerical results on a standard set of bilevel optimization problems show the effectiveness of our new approaches.

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双层优化问题的非精确直接搜索方法
在这项工作中,我们为双层优化(BO)问题的求解引入了新的直接搜索方案。我们的方法依赖于下层问题的固定精度黑盒子甲骨文,并同时处理光滑和潜在非光滑真实目标。因此,我们首次在文献中分析了这些情况下的直接搜索方案,给出了近似静止点的收敛保证,以及光滑情况下的复杂度边界。我们还首次提出了适用于 BO 的网格自适应直接搜索方案。对一组标准双层优化问题的初步数值结果表明了我们新方法的有效性。
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来源期刊
CiteScore
3.70
自引率
9.10%
发文量
91
审稿时长
10 months
期刊介绍: Computational Optimization and Applications is a peer reviewed journal that is committed to timely publication of research and tutorial papers on the analysis and development of computational algorithms and modeling technology for optimization. Algorithms either for general classes of optimization problems or for more specific applied problems are of interest. Stochastic algorithms as well as deterministic algorithms will be considered. Papers that can provide both theoretical analysis, along with carefully designed computational experiments, are particularly welcome. Topics of interest include, but are not limited to the following: Large Scale Optimization, Unconstrained Optimization, Linear Programming, Quadratic Programming Complementarity Problems, and Variational Inequalities, Constrained Optimization, Nondifferentiable Optimization, Integer Programming, Combinatorial Optimization, Stochastic Optimization, Multiobjective Optimization, Network Optimization, Complexity Theory, Approximations and Error Analysis, Parametric Programming and Sensitivity Analysis, Parallel Computing, Distributed Computing, and Vector Processing, Software, Benchmarks, Numerical Experimentation and Comparisons, Modelling Languages and Systems for Optimization, Automatic Differentiation, Applications in Engineering, Finance, Optimal Control, Optimal Design, Operations Research, Transportation, Economics, Communications, Manufacturing, and Management Science.
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