REVIEW 1 cited by
Benders, Nested Benders and Stochastic Programming: An Intuitive Introduction
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Benders, Nested Benders and Stochastic Programming: An Intuitive Introduction
read the original abstract
This article aims to explain the Nested Benders algorithm for the solution of large-scale stochastic programming problems in a way that is intelligible to someone coming to it for the first time. In doing so it gives an explanation of Benders decomposition and of its application to two-stage stochastic programming problems (also known in this context as the L-shaped method), then extends this to multi-stage problems as the Nested Benders algorithm. The article is aimed at readers with some knowledge of linear and possibly stochastic programming but aims to develop most concepts from simple principles in an understandable way. The focus is on intuitive understanding rather than rigorous proofs.
Forward citations
Cited by 1 Pith paper
-
Combined Stochastic and Robust Optimization for Electric Autonomous Mobility-on-Demand with Nested Benders Decomposition
A stochastic-robust MPC framework with Nested Benders Decomposition for EAMoD reduces median waiting times by up to 36% and electricity costs by over 35% versus baselines in city simulations.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.