A genetic and set partitioning two-phase approach for the vehicle routing problem with time windows
By G. B. Alvarenga, G. Mateus, G. Tomi. Computers & Operations Research, 2007
297 citations recorded by the source corpus.
Subfields: Automotive Engineering, Industrial and Manufacturing Engineering
View Paper: https://www.semanticscholar.org/paper/f03c5776bb7cf51917df45bb666ac0ca6dd4fccc
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
- Thibaut Vidal
- Christian Prins
- Teodor Gabriel Crainic
- Michel Gendreau
- Ramasamy Panneerselvam
- S. Kumar
- Michael Drexl
- Gilbert Laporte
In Industrial and Manufacturing Engineering
- Thibaut Vidal
- Teodor Gabriel Crainic
- Christian Prins
- Michel Gendreau
- Ramasamy Panneerselvam
- S. Kumar
- Michael Schneider
- Michael Drexl
Citations in the corpus
- A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows (2013, background): “Most authors have focused on primarily minimizing fleet size, and then distance, but a few exceptions exist (Alvarenga et al. 2007, Labadi et al. 2008).”
- A Survey on the Vehicle Routing Problem and Its Variants (2012, background): “Authors [31] suggest a genetic and set partitioning two-phase approach for the VRPTW.”
- Heuristics for multi-attribute vehicle routing problems: A survey and synthesis (2013, background): “…constraint programming components to recombine promising elements of solutions into complete solutions (Rochat and Taillard 1995, Tarantilis 2005, Alvarenga et al. 2007, Groër and Golden 2011), or to explore large neighbourhoods based on ruin-and-recreate (Shaw 1998, De Franceschi et al. 2006,…”