A metaheuristic approach to the reliable location routing problem under disruptions

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

Research output: Contribution to journalArticle

24 Citations (Scopus)

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 languageEnglish (US)
Article number1130
Pages (from-to)90-110
Number of pages21
JournalTransportation Research Part E: Logistics and Transportation Review
Volume83
DOIs
StatePublished - Nov 1 2015

Fingerprint

scenario
operating costs
Integer programming
Simulated annealing
Operating costs
Maximum likelihood
heuristics
Identification (control systems)
customer
programming
Sampling
costs
Costs
Routing
Scenarios
Metaheuristics
Disruption
Heuristics
Mixed integer programming
Reallocation

Keywords

  • Facility disruptions
  • Location-routing problem
  • Reliability design
  • Simulated annealing

ASJC Scopus subject areas

  • Business and International Management
  • Management Science and Operations Research
  • Transportation

Cite this

A metaheuristic approach to the reliable location routing problem under disruptions. / Zhang, Ying; Qi, Mingyao; Lin, Wei Hua; Miao, Lixin.

In: Transportation Research Part E: Logistics and Transportation Review, Vol. 83, 1130, 01.11.2015, p. 90-110.

Research output: Contribution to journalArticle

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