Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study

•Robust global supply network design under demand and procurement cost uncertainties.•Flexible and resilience strategies to mitigate the risk of correlated disruptive events.•Efficient parallel Taguchi-based memetic algorithm with a hybrid ALNS.•A real-life case study of a global medical device manu...

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Veröffentlicht in:Transportation research. Part E, Logistics and transportation review Jg. 87; S. 20 - 52
Hauptverfasser: Hasani, Aliakbar, Khosrojerdi, Amirhossein
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Exeter Elsevier India Pvt Ltd 01.03.2016
Elsevier Sequoia S.A
Schlagworte:
Algorithms
Disruption
Disruption management
Effectiveness studies
Fitness landscape analysis
Global supply chain network design
Heuristic
Integer programming
Lagrange multiplier
Networks
Parallel memetic algorithm
Resilience
Resilience strategies
Risk management
Robust optimization
Strategy
Supply chain management
Supply chains
Taguchi methods
Transportation
Uncertainty
Global supply chain network design
Parallel memetic algorithm
Robust optimization
Disruption management
Fitness landscape analysis
Resilience strategies
ISSN:1366-5545, 1878-5794
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Zusammenfassung:•Robust global supply network design under demand and procurement cost uncertainties.•Flexible and resilience strategies to mitigate the risk of correlated disruptive events.•Efficient parallel Taguchi-based memetic algorithm with a hybrid ALNS.•A real-life case study of a global medical device manufacturer company. A mixed-integer, non-linear model is developed for designing robust global supply chain networks under uncertainty. Six resilience strategies are proposed to mitigate the risk of correlated disruptions. In addition, an efficient parallel Taguchi-based memetic algorithm is developed that incorporates a customized hybrid parallel adaptive large neighborhood search. Fitness landscape analysis is used to determine an effective selection of neighborhood structures, while the upper bound found by Lagrangian relaxation heuristic is used to evaluate quality of solutions and effectiveness of the proposed metaheuristic. The model is solved for a real-life case of a global medical device manufacturer to extract managerial insights.
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ISSN:1366-5545
1878-5794
DOI:10.1016/j.tre.2015.12.009