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Route Minimization Heuristic for the Vehicle Routing Problem with Multiple Pauses. / Khmelev, Alexey.

OPERATIONS RESEARCH PROCEEDINGS 2015. ed. / KF Doerner; Ljubic; G Pflug; G Tragler. Springer International Publishing AG, 2017. p. 265-271 (Operations Research Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Khmelev, A 2017, Route Minimization Heuristic for the Vehicle Routing Problem with Multiple Pauses. in KF Doerner, Ljubic, G Pflug & G Tragler (eds), OPERATIONS RESEARCH PROCEEDINGS 2015. Operations Research Proceedings, Springer International Publishing AG, pp. 265-271, Operations Research Conference (OR), Vienna, Austria, 01.09.2015. https://doi.org/10.1007/978-3-319-42902-1_36

APA

Khmelev, A. (2017). Route Minimization Heuristic for the Vehicle Routing Problem with Multiple Pauses. In KF. Doerner, Ljubic, G. Pflug, & G. Tragler (Eds.), OPERATIONS RESEARCH PROCEEDINGS 2015 (pp. 265-271). (Operations Research Proceedings). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-42902-1_36

Vancouver

Khmelev A. Route Minimization Heuristic for the Vehicle Routing Problem with Multiple Pauses. In Doerner KF, Ljubic, Pflug G, Tragler G, editors, OPERATIONS RESEARCH PROCEEDINGS 2015. Springer International Publishing AG. 2017. p. 265-271. (Operations Research Proceedings). doi: 10.1007/978-3-319-42902-1_36

Author

Khmelev, Alexey. / Route Minimization Heuristic for the Vehicle Routing Problem with Multiple Pauses. OPERATIONS RESEARCH PROCEEDINGS 2015. editor / KF Doerner ; Ljubic ; G Pflug ; G Tragler. Springer International Publishing AG, 2017. pp. 265-271 (Operations Research Proceedings).

BibTeX

@inproceedings{3c1ac659bc57419cba06d9a2aa8a2317,
title = "Route Minimization Heuristic for the Vehicle Routing Problem with Multiple Pauses",
abstract = "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.",
author = "Alexey Khmelev",
year = "2017",
month = mar,
day = "8",
doi = "10.1007/978-3-319-42902-1_36",
language = "English",
isbn = "978-3-319-42901-4",
series = "Operations Research Proceedings",
publisher = "Springer International Publishing AG",
pages = "265--271",
editor = "KF Doerner and Ljubic and G Pflug and G Tragler",
booktitle = "OPERATIONS RESEARCH PROCEEDINGS 2015",
address = "Switzerland",
note = "Operations Research Conference (OR) ; Conference date: 01-09-2015 Through 04-09-2015",

}

RIS

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