2023
DOI: 10.1016/j.ejor.2022.11.023
|View full text |Cite
|
Sign up to set email alerts
|

A memetic algorithm for solving rich waste collection problems

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
5

Relationship

1
4

Authors

Journals

citations
Cited by 5 publications
(1 citation statement)
references
References 37 publications
0
1
0
Order By: Relevance
“…Benjamin and Beasley (2013) use this procedure based on dynamic programming to improve their heuristics for their VRP with time windows. For a real-life rich WaCo problem in Belgium, Lavigne et al (2022) present a memetic algorithm with a sequential split procedure, which splits a giant tour into single routes, inserts IFs, and further splits the pick-ups, if profitable, before improving these solutions via local search. Inspired by a WaCo problem in Switzerland, Markov et al (2016) solve a VRP with IF, a heterogeneous fleet, a flexible vehicle-depot assignment, time windows, driver breaks and site dependencies, i. e. not all streets are accessible for all vehicles, for which they propose a MILP and a multiple neighborhood search heuristic.…”
Section: Vrps With Intermediate Facilitiesmentioning
confidence: 99%
“…Benjamin and Beasley (2013) use this procedure based on dynamic programming to improve their heuristics for their VRP with time windows. For a real-life rich WaCo problem in Belgium, Lavigne et al (2022) present a memetic algorithm with a sequential split procedure, which splits a giant tour into single routes, inserts IFs, and further splits the pick-ups, if profitable, before improving these solutions via local search. Inspired by a WaCo problem in Switzerland, Markov et al (2016) solve a VRP with IF, a heterogeneous fleet, a flexible vehicle-depot assignment, time windows, driver breaks and site dependencies, i. e. not all streets are accessible for all vehicles, for which they propose a MILP and a multiple neighborhood search heuristic.…”
Section: Vrps With Intermediate Facilitiesmentioning
confidence: 99%