Distributionally robust optimization: A review
H Rahimian, S Mehrotra - arXiv preprint arXiv:1908.05659, 2019 - arxiv.org
The concepts of risk-aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. Statistical learning community has also …
have developed significantly over the last decade. Statistical learning community has also …
Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathematical programming
C Ning, F You - Computers & Chemical Engineering, 2019 - Elsevier
This paper reviews recent advances in the field of optimization under uncertainty via a
modern data lens, highlights key research challenges and promise of data-driven …
modern data lens, highlights key research challenges and promise of data-driven …
Frameworks and results in distributionally robust optimization
H Rahimian, S Mehrotra - Open Journal of Mathematical Optimization, 2022 - numdam.org
The concepts of risk aversion, chance-constrained optimization, and robust optimization
have developed significantly over the last decade. The statistical learning community has …
have developed significantly over the last decade. The statistical learning community has …
Data-driven chance constrained programs over Wasserstein balls
We provide an exact deterministic reformulation for data-driven, chance-constrained
programs over Wasserstein balls. For individual chance constraints as well as joint chance …
programs over Wasserstein balls. For individual chance constraints as well as joint chance …
[图书][B] Moment and Polynomial Optimization
J Nie - 2023 - SIAM
Moment and polynomial optimization has received high attention in recent decades. It has
beautiful theory and efficient methods, as well as broad applications for various …
beautiful theory and efficient methods, as well as broad applications for various …
Sustainable supplier selection and order allocation: Distributionally robust goal programming model and tractable approximation
R Jia, Y Liu, X Bai - Computers & Industrial Engineering, 2020 - Elsevier
A challenge of planning real-life sustainable supplier selection and order allocation (SS/OA)
problems for purchasing companies is to gather the extensive data and exact distributions of …
problems for purchasing companies is to gather the extensive data and exact distributions of …
Optimizing bike rebalancing strategies in free-floating bike-sharing systems: An enhanced distributionally robust approach
Bike-sharing systems are important components of urban transportation systems that
facilitate short-distance travel. In recent years, free-floating bike-sharing systems have …
facilitate short-distance travel. In recent years, free-floating bike-sharing systems have …
A multi-objective distributionally robust model for sustainable last mile relief network design problem
Natural disasters not only inflict massive life and economic losses but also result in
psychological damage to survivors, at times even causing social unrest. It is necessary to …
psychological damage to survivors, at times even causing social unrest. It is necessary to …
The distributionally robust chance-constrained vehicle routing problem
S Ghosal, W Wiesemann - Operations Research, 2020 - pubsonline.informs.org
We study a variant of the capacitated vehicle routing problem (CVRP), which asks for the
cost-optimal delivery of a single product to geographically dispersed customers through a …
cost-optimal delivery of a single product to geographically dispersed customers through a …
A survey of nonlinear robust optimization
Robust optimization (RO) has attracted much attention from the optimization community over
the past decade. RO is dedicated to solving optimization problems subject to uncertainty …
the past decade. RO is dedicated to solving optimization problems subject to uncertainty …