论文信息 - A robust robust optimization result

A robust robust optimization result

We study the loss in objective value when an inaccurate objective is optimized instead of the true one, and show that “on average” this loss is very small, for an arbitrary compact feasible region.

Michael J. Todd | Martina Gancarova

[1] Shang-Hua Teng,et al. Smoothed Analysis of Multiobjective Optimization , 2009, 2009 50th Annual IEEE Symposium on Foundations of Computer Science.

[2] C. Hillermeier. Nonlinear Multiobjective Optimization: A Generalized Homotopy Approach , 2001 .

[3] Laurent El Ghaoui,et al. Robust Optimization , 2021, ICORES.

[4] Arkadi Nemirovski,et al. Robust solutions of Linear Programming problems contaminated with uncertain data , 2000, Math. Program..

[5] Laurent El Ghaoui,et al. Foreword: special issue on robust optimization , 2006, Math. Program..

[6] J. Dennis,et al. A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems , 1997 .

[7] Arkadi Nemirovski,et al. Robust solutions of uncertain linear programs , 1999, Oper. Res. Lett..

[8] Melvyn Sim,et al. Tractable Approximations to Robust Conic Optimization Problems , 2006, Math. Program..

[9] René Beier,et al. Random knapsack in expected polynomial time , 2003, STOC '03.