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Exact and hyper-heuristic solutions for the distribution-installation problem from the VeRoLog 2019 challenge

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Exact and hyper-heuristic solutions for the distribution-installation problem from the VeRoLog 2019 challenge. / Kheiri, Ahmed; Ahmed, Leena; Boyacı, Burak; Gromicho, Joaquim; Mumford, Christine ; Özcan, Ender; Dirikoc, Ali Selim.

In: Networks, Vol. 76, No. 2, 01.09.2020, p. 294-319.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Kheiri, A, Ahmed, L, Boyacı, B, Gromicho, J, Mumford, C, Özcan, E & Dirikoc, AS 2020, 'Exact and hyper-heuristic solutions for the distribution-installation problem from the VeRoLog 2019 challenge', Networks, vol. 76, no. 2, pp. 294-319. https://doi.org/10.1002/net.21962

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Kheiri, Ahmed ; Ahmed, Leena ; Boyacı, Burak ; Gromicho, Joaquim ; Mumford, Christine ; Özcan, Ender ; Dirikoc, Ali Selim. / Exact and hyper-heuristic solutions for the distribution-installation problem from the VeRoLog 2019 challenge. In: Networks. 2020 ; Vol. 76, No. 2. pp. 294-319.

Bibtex

@article{bde64c84411746e6b07615d472359adf,
title = "Exact and hyper-heuristic solutions for the distribution-installation problem from the VeRoLog 2019 challenge",
abstract = "This work tackles a rich vehicle routing problem (VRP) problem integrating a capacitated vehicle routing problem with time windows (CVRPTW), and a service technician routing and scheduling problem (STRSP) for delivering various equipment based on customers' requests, and the subsequent installation by a number of technicians. The main objective is to reduce the overall costs of hired resources, and the total transportation costs of trucks/technicians. The problem was the topic of the fourth edition of the VeRoLog Solver Challenge in cooperation with the ORTEC company. Our contribution to research is the development of a mathematical model for this problem and a novel hyper‐heuristic algorithm to solve the problem based on a population of solutions. Experimental results on two datasets of small and real‐world size revealed the success of the hyper‐heuristic approach in finding optimal solutions in a shorter computational time, when compared to our exact model. The results of the large size dataset were also compared to the results of the eight finalists in the competition and were found to be competitive, proving the potential of our developed hyper‐heuristic framework.",
author = "Ahmed Kheiri and Leena Ahmed and Burak Boyacı and Joaquim Gromicho and Christine Mumford and Ender {\"O}zcan and Dirikoc, {Ali Selim}",
year = "2020",
month = sep,
day = "1",
doi = "10.1002/net.21962",
language = "English",
volume = "76",
pages = "294--319",
journal = "Networks",
issn = "0028-3045",
publisher = "Blackwell-Wiley",
number = "2",

}

RIS

TY - JOUR

T1 - Exact and hyper-heuristic solutions for the distribution-installation problem from the VeRoLog 2019 challenge

AU - Kheiri, Ahmed

AU - Ahmed, Leena

AU - Boyacı, Burak

AU - Gromicho, Joaquim

AU - Mumford, Christine

AU - Özcan, Ender

AU - Dirikoc, Ali Selim

PY - 2020/9/1

Y1 - 2020/9/1

N2 - This work tackles a rich vehicle routing problem (VRP) problem integrating a capacitated vehicle routing problem with time windows (CVRPTW), and a service technician routing and scheduling problem (STRSP) for delivering various equipment based on customers' requests, and the subsequent installation by a number of technicians. The main objective is to reduce the overall costs of hired resources, and the total transportation costs of trucks/technicians. The problem was the topic of the fourth edition of the VeRoLog Solver Challenge in cooperation with the ORTEC company. Our contribution to research is the development of a mathematical model for this problem and a novel hyper‐heuristic algorithm to solve the problem based on a population of solutions. Experimental results on two datasets of small and real‐world size revealed the success of the hyper‐heuristic approach in finding optimal solutions in a shorter computational time, when compared to our exact model. The results of the large size dataset were also compared to the results of the eight finalists in the competition and were found to be competitive, proving the potential of our developed hyper‐heuristic framework.

AB - This work tackles a rich vehicle routing problem (VRP) problem integrating a capacitated vehicle routing problem with time windows (CVRPTW), and a service technician routing and scheduling problem (STRSP) for delivering various equipment based on customers' requests, and the subsequent installation by a number of technicians. The main objective is to reduce the overall costs of hired resources, and the total transportation costs of trucks/technicians. The problem was the topic of the fourth edition of the VeRoLog Solver Challenge in cooperation with the ORTEC company. Our contribution to research is the development of a mathematical model for this problem and a novel hyper‐heuristic algorithm to solve the problem based on a population of solutions. Experimental results on two datasets of small and real‐world size revealed the success of the hyper‐heuristic approach in finding optimal solutions in a shorter computational time, when compared to our exact model. The results of the large size dataset were also compared to the results of the eight finalists in the competition and were found to be competitive, proving the potential of our developed hyper‐heuristic framework.

U2 - 10.1002/net.21962

DO - 10.1002/net.21962

M3 - Journal article

VL - 76

SP - 294

EP - 319

JO - Networks

JF - Networks

SN - 0028-3045

IS - 2

ER -