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The Variable Neighborhood Search for a Consistent Vehicle Routing Problem under the Shift Length Constraints. / Kulachenko, I. N.; Kononova, P. A.; Kochetov, Y. A. и др.

в: Ifac papersonline, Том 52, № 13, 09.2019, стр. 2314-2319.

Результаты исследований: Научные публикации в периодических изданияхстатья по материалам конференцииРецензирование

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Kulachenko IN, Kononova PA, Kochetov YA, Kurochkin AA. The Variable Neighborhood Search for a Consistent Vehicle Routing Problem under the Shift Length Constraints. Ifac papersonline. 2019 сент.;52(13):2314-2319. doi: 10.1016/j.ifacol.2019.11.551

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BibTeX

@article{3b15b564b93e4ff6a9cdd73ed579df1e,
title = "The Variable Neighborhood Search for a Consistent Vehicle Routing Problem under the Shift Length Constraints",
abstract = "This paper addresses a new real-world application of vehicle routing planning in a finite time horizon. A company in the small package shipping industry has a limited fleet of identical vehicles in some depots and must serve a set of clients. There is a frequency for each client stating how often this client must be visited. Time intervals between two consecutive visits must be the same but the visiting schedule is flexible. To get some competitive advantage, a company tries to increase the service quality. To this end, each client should be visited by one driver only. The goal is to minimize the total traveling distance for all vehicles over the planning horizon under the frequency constraints and driver shift length constraints. We present an integer linear programming model for this new consistent vehicle routing problem. To find near optimal solutions, we design the Variable Neighborhood Search metaheuristic with nine neighborhood structures. The driver shift length constraints are penalized and included in the objective function. Empirical results for real test instances from Orenburg region in Russia with up to 900 clients and four weeks in the planning horizon are discussed.",
keywords = "Operations research, mathematical models, optimization problems, time scheduling, search methods, routing algorithms, computer experiments, LOCAL SEARCH, Routing algorithms, Computer experiments, Search methods, Mathematical models, Optimization problems, Time scheduling",
author = "Kulachenko, {I. N.} and Kononova, {P. A.} and Kochetov, {Y. A.} and Kurochkin, {A. A.}",
year = "2019",
month = sep,
doi = "10.1016/j.ifacol.2019.11.551",
language = "English",
volume = "52",
pages = "2314--2319",
journal = "Ifac papersonline",
issn = "2405-8963",
publisher = "Elsevier",
number = "13",
note = "9th IFAC/IFIP/IFORS/IISE/INFORMS Conference on Manufacturing Modelling, Management and Control (IFAC MIM) ; Conference date: 28-08-2019 Through 30-08-2019",

}

RIS

TY - JOUR

T1 - The Variable Neighborhood Search for a Consistent Vehicle Routing Problem under the Shift Length Constraints

AU - Kulachenko, I. N.

AU - Kononova, P. A.

AU - Kochetov, Y. A.

AU - Kurochkin, A. A.

PY - 2019/9

Y1 - 2019/9

N2 - This paper addresses a new real-world application of vehicle routing planning in a finite time horizon. A company in the small package shipping industry has a limited fleet of identical vehicles in some depots and must serve a set of clients. There is a frequency for each client stating how often this client must be visited. Time intervals between two consecutive visits must be the same but the visiting schedule is flexible. To get some competitive advantage, a company tries to increase the service quality. To this end, each client should be visited by one driver only. The goal is to minimize the total traveling distance for all vehicles over the planning horizon under the frequency constraints and driver shift length constraints. We present an integer linear programming model for this new consistent vehicle routing problem. To find near optimal solutions, we design the Variable Neighborhood Search metaheuristic with nine neighborhood structures. The driver shift length constraints are penalized and included in the objective function. Empirical results for real test instances from Orenburg region in Russia with up to 900 clients and four weeks in the planning horizon are discussed.

AB - This paper addresses a new real-world application of vehicle routing planning in a finite time horizon. A company in the small package shipping industry has a limited fleet of identical vehicles in some depots and must serve a set of clients. There is a frequency for each client stating how often this client must be visited. Time intervals between two consecutive visits must be the same but the visiting schedule is flexible. To get some competitive advantage, a company tries to increase the service quality. To this end, each client should be visited by one driver only. The goal is to minimize the total traveling distance for all vehicles over the planning horizon under the frequency constraints and driver shift length constraints. We present an integer linear programming model for this new consistent vehicle routing problem. To find near optimal solutions, we design the Variable Neighborhood Search metaheuristic with nine neighborhood structures. The driver shift length constraints are penalized and included in the objective function. Empirical results for real test instances from Orenburg region in Russia with up to 900 clients and four weeks in the planning horizon are discussed.

KW - Operations research

KW - mathematical models

KW - optimization problems

KW - time scheduling

KW - search methods

KW - routing algorithms

KW - computer experiments

KW - LOCAL SEARCH

KW - Routing algorithms

KW - Computer experiments

KW - Search methods

KW - Mathematical models

KW - Optimization problems

KW - Time scheduling

UR - http://www.scopus.com/inward/record.url?scp=85078951795&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2019.11.551

DO - 10.1016/j.ifacol.2019.11.551

M3 - Conference article

VL - 52

SP - 2314

EP - 2319

JO - Ifac papersonline

JF - Ifac papersonline

SN - 2405-8963

IS - 13

T2 - 9th IFAC/IFIP/IFORS/IISE/INFORMS Conference on Manufacturing Modelling, Management and Control (IFAC MIM)

Y2 - 28 August 2019 through 30 August 2019

ER -

ID: 23292381