A survey of contextual optimization methods for decision-making under uncertainty
Recently there has been a surge of interest in operations research (OR) and the machine
learning (ML) community in combining prediction algorithms and optimization techniques to …
learning (ML) community in combining prediction algorithms and optimization techniques to …
A review of robust operations management under model uncertainty
M Lu, ZJM Shen - Production and Operations Management, 2021 - journals.sagepub.com
Over the past two decades, there has been explosive growth in the application of robust
optimization in operations management (robust OM), fueled by both significant advances in …
optimization in operations management (robust OM), fueled by both significant advances in …
Testing facility location and dynamic capacity planning for pandemics with demand uncertainty
The outbreak of coronavirus disease 2019 (COVID-19) has seriously affected the whole
world, and epidemic research has attracted increasing amounts of scholarly attention …
world, and epidemic research has attracted increasing amounts of scholarly attention …
Wasserstein distributionally robust chance-constrained optimization for energy and reserve dispatch: An exact and physically-bounded formulation
In the context of transition towards sustainable, cost-efficient and reliable energy systems,
the improvement of current energy and reserve dispatch models is crucial to properly cope …
the improvement of current energy and reserve dispatch models is crucial to properly cope …
Multi-stage robust dispatch considering demand response under decision-dependent uncertainty
Demand response (DR) programs create incentives to effectively exploit the hidden
operational flexibility of loads for better supporting power system operations. However, DR …
operational flexibility of loads for better supporting power system operations. However, DR …
A two-stage robust approach to integrated station location and rebalancing vehicle service design in bike-sharing systems
A bike-sharing system is a shared mobility mechanism that provides an alternative
transportation mode for short trips with almost no added travel speed loss. However, this …
transportation mode for short trips with almost no added travel speed loss. However, this …
Robust optimization for energy-aware cryptocurrency farm location with renewable energy
The cryptocurrency industry has changed the human life and accelerated financial
exchange in this decade. Many investors want to invest in this industry and establish …
exchange in this decade. Many investors want to invest in this industry and establish …
Multi-stage distributionally robust optimization for hybrid energy storage in regional integrated energy system considering robustness and nonanticipativity
F Han, J Zeng, J Lin, C Gao - Energy, 2023 - Elsevier
Hybrid energy storage system (HESS) has advantages in coping with the uncertainty of
renewable energy and improving the stability of regional integrated energy systems (RIES) …
renewable energy and improving the stability of regional integrated energy systems (RIES) …
Multistage distributionally robust mixed-integer programming with decision-dependent moment-based ambiguity sets
We study multistage distributionally robust mixed-integer programs under endogenous
uncertainty, where the probability distribution of stage-wise uncertainty depends on the …
uncertainty, where the probability distribution of stage-wise uncertainty depends on the …
Robust facility location under demand uncertainty and facility disruptions
Facility location decision is strategic: the construction of a new facility is typically costly and
the impact of the decision is long-lasting. Environmental changes, such as population shift …
the impact of the decision is long-lasting. Environmental changes, such as population shift …