A Product-Design-Change-Based Recovery Control Algorithm for Supply Chain Disruption Problem

In very recent years, large-scale disruptions brought by major global and local emergencies have posed many challenges with respect to the recovery control of supply chain systems. This work investigates a problem regarding the optimal control of a supply chain by considering product design change i...

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Bibliographic Details
Published in:Electronics (Basel) 2023-06, Vol.12 (12), p.2552
Main Authors: Chen, Jingze, Kang, Haodong, Wang, Hongfeng
Format: Article
Language:English
Subjects:
Algorithms
Ant colony optimization
Control algorithms
Control systems
Control theory
COVID-19
Decision making
Design optimization
Disruption
Emergencies
Heuristic
Integer programming
Inventory
Literature reviews
Logistics
Manufacturers
Manufacturing
Mathematical models
Mathematical optimization
Optimal control
Optimization
Optimization models
Pandemics
Product design
Product development
Production capacity
Profits
Recovery
Suppliers
Supply chains
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Summary:In very recent years, large-scale disruptions brought by major global and local emergencies have posed many challenges with respect to the recovery control of supply chain systems. This work investigates a problem regarding the optimal control of a supply chain by considering product design change in order to enable manufacturers to recover their disrupted supply chain quickly. A two-layer optimization model is developed, in which the lower model is used to optimize the product design change path, and the upper model is used to select the appropriate alternative suppliers and schedule the delivery of customer orders. To solve the developed model, a hybrid ant colony optimization (HACO) algorithm is designed, which is combined with a Gurobi solver and uses some special strategies. The validity of the proposed algorithm is illustrated experimentally through computational tests and systematic comparison with the existing methods. It is reported that the losses caused by supply chain disruptions are reduced significantly. The proposed model and algorithm can provide a potentially useful tool that can help manufacturers decide upon the optimal form of recovery control when a supply chain system experiences a massive supply disruption.
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics12122552