Simulation-optimization methods for designing and assessing resilient supply chain networks under uncertainty scenarios: A review

• Published in: Simulation modelling practice and theory Vol. 106; p. 102166
• Main Authors: Tordecilla, Rafael D., Juan, Angel A., Montoya-Torres, Jairo R., Quintero-Araujo, Carlos L., Panadero, Javier
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.01.2021
• Subjects: Metaheuristics; Resilient supply chain networks design; Simulation-optimization methods; Uncertainty scenarios; Uncertainty scenarios; Resilient supply chain networks design; Simulation-optimization methods; Metaheuristics
• ISSN: 1569-190X; 1878-1462
• DOI: 10.1016/j.simpat.2020.102166

The design of supply chain networks (SCNs) aims at determining the number, location, and capacity of production facilities, as well as the allocation of markets (customers) and suppliers to one or more of these facilities. This paper reviews the existing literature on the use of simulation-optimization methods in the design of resilient SCNs. From this review, we classify some of the many works in the topic according to factors such as their methodology, the approach they use to deal with uncertainty and risk, etc. The paper also identifies several research opportunities, such as the inclusion of multiple criteria (e.g., monetary, environmental, and social dimensions) during the design-optimization process and the convenience of considering hybrid approaches combining metaheuristic algorithms, simulation, and machine learning methods to account for uncertainty and dynamic conditions, respectively.