A model for a reliable single allocation hub network design under massive disruption

Mohsen Yahyaei, Mahdi Bashiri, Marcus Randall

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Hub facilities may fail to operate in networks because of accidental failures such as natural disasters. In this paper, a quadratic model was presented for a reliable single allocation hub network under massive random failure of hub facilities which more than one hub may be disrupted in a route. It determines the location of the hub facilities and the primal allocation of non-hub nodes. It also determines the backup allocation in case of failure of the primal hub. First, a new lexicographic form of a bi-objective quadratic model is presented where the first objective maximizes served demands or equivalently, minimizes lost flows and the second objective minimizes total cost under a to massive disruption in the network. Then, by adding a structure-based constraint, the model is transformed to a single objective one. A linearization technique reported in the literature is applied on the quadratic model to convert it into classic linear zero–one mixed integer model while enhancing it by finding tighter bounds. The tight bounds’ technique is compared with other techniques in terms of computational time and its better performance was approved in some problem instances. Finally, due to the NP-hardness of the problem, an iterated local search algorithm was developed to solve large sized instances in a reasonable computational time and the computational results confirm the efficiency of the proposed heuristic, ILS can solve all CAB and IAD data set instances in less than 15 and 24 seconds, respectively. Moreover, the proposed model was compared with the classical hub network using a network performance measure, and the results show the increased efficiency of the model.
Original languageEnglish
Article number105561
Number of pages14
JournalApplied Soft Computing
Volume82
Early online date18 Jun 2019
DOIs
Publication statusPublished - Sep 2019

Fingerprint

Network performance
Linearization
Disasters
Hardness
Costs

Cite this

@article{0217eeeca20b483793c32d4d253f39a8,
title = "A model for a reliable single allocation hub network design under massive disruption",
abstract = "Hub facilities may fail to operate in networks because of accidental failures such as natural disasters. In this paper, a quadratic model was presented for a reliable single allocation hub network under massive random failure of hub facilities which more than one hub may be disrupted in a route. It determines the location of the hub facilities and the primal allocation of non-hub nodes. It also determines the backup allocation in case of failure of the primal hub. First, a new lexicographic form of a bi-objective quadratic model is presented where the first objective maximizes served demands or equivalently, minimizes lost flows and the second objective minimizes total cost under a to massive disruption in the network. Then, by adding a structure-based constraint, the model is transformed to a single objective one. A linearization technique reported in the literature is applied on the quadratic model to convert it into classic linear zero–one mixed integer model while enhancing it by finding tighter bounds. The tight bounds’ technique is compared with other techniques in terms of computational time and its better performance was approved in some problem instances. Finally, due to the NP-hardness of the problem, an iterated local search algorithm was developed to solve large sized instances in a reasonable computational time and the computational results confirm the efficiency of the proposed heuristic, ILS can solve all CAB and IAD data set instances in less than 15 and 24 seconds, respectively. Moreover, the proposed model was compared with the classical hub network using a network performance measure, and the results show the increased efficiency of the model.",
author = "Mohsen Yahyaei and Mahdi Bashiri and Marcus Randall",
year = "2019",
month = "9",
doi = "10.1016/j.asoc.2019.105561",
language = "English",
volume = "82",
journal = "Applied Soft Computing",
issn = "1568-4946",
publisher = "Elsevier BV",

}

A model for a reliable single allocation hub network design under massive disruption. / Yahyaei, Mohsen; Bashiri, Mahdi; Randall, Marcus.

In: Applied Soft Computing, Vol. 82, 105561, 09.2019.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - A model for a reliable single allocation hub network design under massive disruption

AU - Yahyaei, Mohsen

AU - Bashiri, Mahdi

AU - Randall, Marcus

PY - 2019/9

Y1 - 2019/9

N2 - Hub facilities may fail to operate in networks because of accidental failures such as natural disasters. In this paper, a quadratic model was presented for a reliable single allocation hub network under massive random failure of hub facilities which more than one hub may be disrupted in a route. It determines the location of the hub facilities and the primal allocation of non-hub nodes. It also determines the backup allocation in case of failure of the primal hub. First, a new lexicographic form of a bi-objective quadratic model is presented where the first objective maximizes served demands or equivalently, minimizes lost flows and the second objective minimizes total cost under a to massive disruption in the network. Then, by adding a structure-based constraint, the model is transformed to a single objective one. A linearization technique reported in the literature is applied on the quadratic model to convert it into classic linear zero–one mixed integer model while enhancing it by finding tighter bounds. The tight bounds’ technique is compared with other techniques in terms of computational time and its better performance was approved in some problem instances. Finally, due to the NP-hardness of the problem, an iterated local search algorithm was developed to solve large sized instances in a reasonable computational time and the computational results confirm the efficiency of the proposed heuristic, ILS can solve all CAB and IAD data set instances in less than 15 and 24 seconds, respectively. Moreover, the proposed model was compared with the classical hub network using a network performance measure, and the results show the increased efficiency of the model.

AB - Hub facilities may fail to operate in networks because of accidental failures such as natural disasters. In this paper, a quadratic model was presented for a reliable single allocation hub network under massive random failure of hub facilities which more than one hub may be disrupted in a route. It determines the location of the hub facilities and the primal allocation of non-hub nodes. It also determines the backup allocation in case of failure of the primal hub. First, a new lexicographic form of a bi-objective quadratic model is presented where the first objective maximizes served demands or equivalently, minimizes lost flows and the second objective minimizes total cost under a to massive disruption in the network. Then, by adding a structure-based constraint, the model is transformed to a single objective one. A linearization technique reported in the literature is applied on the quadratic model to convert it into classic linear zero–one mixed integer model while enhancing it by finding tighter bounds. The tight bounds’ technique is compared with other techniques in terms of computational time and its better performance was approved in some problem instances. Finally, due to the NP-hardness of the problem, an iterated local search algorithm was developed to solve large sized instances in a reasonable computational time and the computational results confirm the efficiency of the proposed heuristic, ILS can solve all CAB and IAD data set instances in less than 15 and 24 seconds, respectively. Moreover, the proposed model was compared with the classical hub network using a network performance measure, and the results show the increased efficiency of the model.

UR - http://www.scopus.com/inward/record.url?scp=85067632365&partnerID=8YFLogxK

U2 - 10.1016/j.asoc.2019.105561

DO - 10.1016/j.asoc.2019.105561

M3 - Article

VL - 82

JO - Applied Soft Computing

JF - Applied Soft Computing

SN - 1568-4946

M1 - 105561

ER -