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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| Vydáno v: | Transportation research. Part E, Logistics and transportation review Ročník 87; s. 20 - 52 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Exeter
Elsevier India Pvt Ltd
01.03.2016
Elsevier Sequoia S.A |
| Témata: | |
| ISSN: | 1366-5545, 1878-5794 |
| On-line přístup: | Získat plný text |
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| Abstract | •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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| AbstractList | 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. •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. |
| Author | Khosrojerdi, Amirhossein Hasani, Aliakbar |
| Author_xml | – sequence: 1 givenname: Aliakbar surname: Hasani fullname: Hasani, Aliakbar email: aa.hasani@shahroodut.ac.ir organization: School of Industrial Engineering and Management, University of Shahrood, Shahrood, Iran – sequence: 2 givenname: Amirhossein surname: Khosrojerdi fullname: Khosrojerdi, Amirhossein organization: School of Industrial and Systems Engineering, University of Oklahoma, Norman, OK 73019, USA |
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| SubjectTerms | 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 |
| Title | Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study |
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