Research Article

Research on MAS-Based Supply Chain Resilience and Its Self-Organized Criticality

Table 2

Quantitative studies on supply chain resilience.

AuthorsMethodsMain works and findings

Priya Datta et al. [9]Agent-based computational modellingThis literature studied complex multiproduct and multicountry supply chain subject to demand variability and production and distribution capacity constraints, which aimed to improve operational resilience.

Ratick et al. [10]Linear programmingThe literature used set cover location modeling to show that it is important to take into account potential exposure of facilities when designing supply chains.

Colicchia et al. [11]Simulation applied to real scenarioThis literature identified a set of approaches to manage risks to enhance supply chain resilience. Mitigation strategies do not influence lead-time variability but can reduce lead-time average, which will lead to resilience.

Zhao et al. [12]The simulation analysis of military security networkThis literature analyzed resilience of supply network topology structure under random attacks and attempted attacks from the aspects of availability, connectivity, accessibility, and so forth.

Geng et al. [13]The simulation analysis of cluster supply chainThis literature analyzed dynamic evolution process based on cascading effect mode when cluster supply chain failure happens, which helped to illustrate that the root of vulnerability lies in cascading failure, while self-organization is the key to resilient recovery.

Pettit et al. [14]Questionnaire surveyThis literature developed a measurement tool titled the Supply Chain Resilience Assessment and Management. Critical linkages are uncovered between the inherent vulnerability factors and controllable capability factors.

Francis and Bekera [15]The simulation analysis of electric power networkThis literature proposed a framework which is focused on the achievement of three resilience capacities: adaptive capacity, absorptive capacity, and recoverability.