Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Route Minimization Heuristic for the Vehicle Routing Problem with Multiple Pauses. / Khmelev, Alexey.
OPERATIONS RESEARCH PROCEEDINGS 2015. ред. / KF Doerner; Ljubic; G Pflug; G Tragler. Springer International Publishing AG, 2017. стр. 265-271 (Operations Research Proceedings).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Route Minimization Heuristic for the Vehicle Routing Problem with Multiple Pauses
AU - Khmelev, Alexey
PY - 2017/3/8
Y1 - 2017/3/8
N2 - In this work we introduce the vehicle routing problem with multiple pauses, where the fleet is heterogeneous in terms of capacity and drivers availability. Each shift has a time interval when the driver is available and a set of breaks that needs to be scheduled in the route during this shift. The objective is to minimize the number of vehicles and the travel distance. To tackle large instances, we develop a three-phase local search algorithm taking multiple breaks into account by introducing an ejection pool and randomized variable neighborhood descent as local improvement procedure. For effective break scheduling, we develop a special dynamic programming routine. Computational experiments are done on the data set provided by a delivery company situated in Novosibirsk, Russia. The instances contain 1000 customers and 30 vehicles. Experiments show effectiveness of our algorithm. It substantially reduces the fleet and travel distance.
AB - In this work we introduce the vehicle routing problem with multiple pauses, where the fleet is heterogeneous in terms of capacity and drivers availability. Each shift has a time interval when the driver is available and a set of breaks that needs to be scheduled in the route during this shift. The objective is to minimize the number of vehicles and the travel distance. To tackle large instances, we develop a three-phase local search algorithm taking multiple breaks into account by introducing an ejection pool and randomized variable neighborhood descent as local improvement procedure. For effective break scheduling, we develop a special dynamic programming routine. Computational experiments are done on the data set provided by a delivery company situated in Novosibirsk, Russia. The instances contain 1000 customers and 30 vehicles. Experiments show effectiveness of our algorithm. It substantially reduces the fleet and travel distance.
U2 - 10.1007/978-3-319-42902-1_36
DO - 10.1007/978-3-319-42902-1_36
M3 - Conference contribution
SN - 978-3-319-42901-4
T3 - Operations Research Proceedings
SP - 265
EP - 271
BT - OPERATIONS RESEARCH PROCEEDINGS 2015
A2 - Doerner, KF
A2 - Ljubic, null
A2 - Pflug, G
A2 - Tragler, G
PB - Springer International Publishing AG
T2 - Operations Research Conference (OR)
Y2 - 1 September 2015 through 4 September 2015
ER -
ID: 18873164