A metaheuristic approach to the reliable location routing problem under disruptions

Ying Zhang; Mingyao Qi; Wei Hua Lin; Lixin Miao

doi:10.1016/j.tre.2015.09.001

A metaheuristic approach to the reliable location routing problem under disruptions

Ying Zhang, Mingyao Qi, Wei Hua Lin, Lixin Miao

Research output: Contribution to journal › Article › peer-review

76 Scopus citations

Abstract

This paper examines a reliable capacitated location-routing problem in which depots are randomly disrupted. Customers whose depots fail must be reinserted into the routes of surviving depots. We present a scenario-based mixed-integer programming model to optimize depot location, outbound delivery routing, and backup plans. We design a metaheuristic algorithm that is based on a maximum-likelihood sampling method, route-reallocation improvement, two-stage neighborhood search and simulated annealing. Numerical tests show that the heuristic is able to generate results that would keep operating costs and failure costs well balanced. Managerial insights on scenario identification, facility deployment and model simplification are drawn.

Original language	English (US)
Pages (from-to)	90-110
Number of pages	21
Journal	Transportation Research Part E: Logistics and Transportation Review
Volume	83
DOIs	https://doi.org/10.1016/j.tre.2015.09.001
State	Published - Nov 1 2015

Keywords

Facility disruptions
Location-routing problem
Reliability design
Simulated annealing

ASJC Scopus subject areas

Business and International Management
Civil and Structural Engineering
Transportation

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10.1016/j.tre.2015.09.001

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title = "A metaheuristic approach to the reliable location routing problem under disruptions",

abstract = "This paper examines a reliable capacitated location-routing problem in which depots are randomly disrupted. Customers whose depots fail must be reinserted into the routes of surviving depots. We present a scenario-based mixed-integer programming model to optimize depot location, outbound delivery routing, and backup plans. We design a metaheuristic algorithm that is based on a maximum-likelihood sampling method, route-reallocation improvement, two-stage neighborhood search and simulated annealing. Numerical tests show that the heuristic is able to generate results that would keep operating costs and failure costs well balanced. Managerial insights on scenario identification, facility deployment and model simplification are drawn.",

keywords = "Facility disruptions, Location-routing problem, Reliability design, Simulated annealing",

author = "Ying Zhang and Mingyao Qi and Lin, {Wei Hua} and Lixin Miao",

note = "Funding Information: The National Natural Science Foundation of China ( 71272030 ), National Key Technology Support Program of China ( 2014BAH23F04 ) and the Science & Technology Foundation of Shenzhen , China ( CXZZ20130321145336439 ) supported this work. The authors would like to thank the anonymous reviewers for their helpful and constructive comments that greatly contributed to improving the final version of the paper. They would also like to thank the Editors for their generous comments and support during the review process. Publisher Copyright: {\textcopyright} 2015 Elsevier Ltd.",

year = "2015",

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doi = "10.1016/j.tre.2015.09.001",

language = "English (US)",

volume = "83",

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journal = "Transportation Research Part E: Logistics and Transportation Review",

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AU - Zhang, Ying

AU - Qi, Mingyao

AU - Lin, Wei Hua

AU - Miao, Lixin

N1 - Funding Information: The National Natural Science Foundation of China ( 71272030 ), National Key Technology Support Program of China ( 2014BAH23F04 ) and the Science & Technology Foundation of Shenzhen , China ( CXZZ20130321145336439 ) supported this work. The authors would like to thank the anonymous reviewers for their helpful and constructive comments that greatly contributed to improving the final version of the paper. They would also like to thank the Editors for their generous comments and support during the review process. Publisher Copyright: © 2015 Elsevier Ltd.

PY - 2015/11/1

Y1 - 2015/11/1

N2 - This paper examines a reliable capacitated location-routing problem in which depots are randomly disrupted. Customers whose depots fail must be reinserted into the routes of surviving depots. We present a scenario-based mixed-integer programming model to optimize depot location, outbound delivery routing, and backup plans. We design a metaheuristic algorithm that is based on a maximum-likelihood sampling method, route-reallocation improvement, two-stage neighborhood search and simulated annealing. Numerical tests show that the heuristic is able to generate results that would keep operating costs and failure costs well balanced. Managerial insights on scenario identification, facility deployment and model simplification are drawn.

AB - This paper examines a reliable capacitated location-routing problem in which depots are randomly disrupted. Customers whose depots fail must be reinserted into the routes of surviving depots. We present a scenario-based mixed-integer programming model to optimize depot location, outbound delivery routing, and backup plans. We design a metaheuristic algorithm that is based on a maximum-likelihood sampling method, route-reallocation improvement, two-stage neighborhood search and simulated annealing. Numerical tests show that the heuristic is able to generate results that would keep operating costs and failure costs well balanced. Managerial insights on scenario identification, facility deployment and model simplification are drawn.

KW - Facility disruptions

KW - Location-routing problem

KW - Reliability design

KW - Simulated annealing

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JO - Transportation Research Part E: Logistics and Transportation Review

JF - Transportation Research Part E: Logistics and Transportation Review

ER -

A metaheuristic approach to the reliable location routing problem under disruptions

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Keywords

ASJC Scopus subject areas

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