Agribusiness supply chain risk management: A review of quantitative decision models
Supply chain risk management is a large and growing field of research. However, within this
field, mathematical models for agricultural products have received relatively little attention …
field, mathematical models for agricultural products have received relatively little attention …
A survey of adjustable robust optimization
Static robust optimization (RO) is a methodology to solve mathematical optimization
problems with uncertain data. The objective of static RO is to find solutions that are immune …
problems with uncertain data. The objective of static RO is to find solutions that are immune …
Differentiable convex optimization layers
Recent work has shown how to embed differentiable optimization problems (that is,
problems whose solutions can be backpropagated through) as layers within deep learning …
problems whose solutions can be backpropagated through) as layers within deep learning …
A practical guide to robust optimization
Robust optimization is a young and active research field that has been mainly developed in
the last 15 years. Robust optimization is very useful for practice, since it is tailored to the …
the last 15 years. Robust optimization is very useful for practice, since it is tailored to the …
A linear programming approach for robust network revenue management in the airline industry
The classical revenue management problem consists of allocating a fixed network capacity
to different customer classes, so as to maximize revenue. This area has been widely applied …
to different customer classes, so as to maximize revenue. This area has been widely applied …
A unified framework for stochastic optimization
WB Powell - European Journal of Operational Research, 2019 - Elsevier
Stochastic optimization is an umbrella term that includes over a dozen fragmented
communities, using a patchwork of sometimes overlap** notational systems with …
communities, using a patchwork of sometimes overlap** notational systems with …
Data-driven robust optimization
The last decade witnessed an explosion in the availability of data for operations research
applications. Motivated by this growing availability, we propose a novel schema for utilizing …
applications. Motivated by this growing availability, we propose a novel schema for utilizing …
[引用][C] Robust Optimization
A Ben-Tal - Princeton University Press google schola, 2009 - books.google.com
Robust optimization is still a relatively new approach to optimization problems affected by
uncertainty, but it has already proved so useful in real applications that it is difficult to tackle …
uncertainty, but it has already proved so useful in real applications that it is difficult to tackle …
Theory and applications of robust optimization
In this paper we survey the primary research, both theoretical and applied, in the area of
robust optimization (RO). Our focus is on the computational attractiveness of RO …
robust optimization (RO). Our focus is on the computational attractiveness of RO …
[HTML][HTML] A robust optimization approach to closed-loop supply chain network design under uncertainty
The concern about significant changes in the business environment (such as customer
demands and transportation costs) has spurred an interest in designing scalable and robust …
demands and transportation costs) has spurred an interest in designing scalable and robust …