An Integer L-Shaped Algorithm for the Capacitated Vehicle Routing Problem with Stochastic Demands
By Gilbert Laporte, F. Louveaux, L. Hamme. Operational Research, 2002
334 citations recorded by the source corpus.
Subfields: Automotive Engineering, Industrial and Manufacturing Engineering, Transportation
View Paper: https://www.semanticscholar.org/paper/f3bd513ebafe8f20ad3fb35b7bb1a8437282a744
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Automotive Engineering
- Richard F. Hartl
- Jakob Puchinger
- Ola Jabali
- Michel Gendreau
- Walter Rei
- Ulrike Ritzinger
- Andrés L. Medaglia
- Christelle Guéret
In Industrial and Manufacturing Engineering
- Michel Gendreau
- Richard F. Hartl
- Jakob Puchinger
- Andrés L. Medaglia
- Christelle Guéret
- Victor Pillac
- Ola Jabali
- Walter Rei
In Transportation
- Michel Gendreau
- Richard F. Hartl
- Walter Rei
- Ulrike Ritzinger
- Ola Jabali
- Jakob Puchinger
- Andrés L. Medaglia
- Christelle Guéret
Citations in the corpus
- A survey on dynamic and stochastic vehicle routing problems (2016, background): “According to Laporte, Louveaux, and van Hamme (2002), problem instances with an EFR ≥ 1 can be considered as difficult.”
- Stochastic Vehicle Routing Problems (2014, positive): “38 / 111 Integer L-shaped algorithm for the VRPSD Main challenges • Approximation ofQ(x) • Hard to obtain a good general lower bound L⇒ (Laporte et al., 2002) • Information provided by optimality cuts is very local • High number of LBF cuts need to be added • Quality of the upper bound • No guarante”
- A review of dynamic vehicle routing problems (2013, background): “Uncertainty may affect any of the input data, yet the three most studied cases are [33]: stochastic customers, where a customer needs to be serviced with a given probability [15,147]; stochastic times, in which either service or travel times are modeled by random variables [79,85,146]; and lastly, s”