Analyzing the Resilience of Complex Supply Network Topologies Against Random and Targeted Disruptions

Abstract

Abstract-In this paper, we study the resilience of supply networks against disruptions and provide insights to supply chain managers on how to construct a resilient supply network from the perspective of complex network topologies. Our goal is to study how different network topologies, which are created from different growth models, affect the network's resilience against both random and targeted disruptions. Of particular interest are situations where the type of disruption is unknown. Using a military logistic network as a case study, we propose new network resilience metrics that reflect the heterogeneous roles (e.g., supply, relay, and demand) of nodes in supply networks. We also present a hybrid and tunable network growth model called Degree and Locality-based Attachment (DLA), in which new nodes make connections based on both degree and locality. Using computer simulations, we compare the resilience of several supply network topologies that are generated with different growth models. The results show that the new resilience metrics can capture important resilience requirements for supply networks very well. We also found that the supply network topology generated by the DLA model provides balanced resilience against both random and targeted disruptions.

Modeling and Simulation for Effectiveness Evaluation of Dynamic Discrete Military Supply Chain Networks

“…However, the supply network optimization problem is NP-hard. Although the traditional methods can evaluate the resilience and reliability of small-scale and static supply chains from the perspective of topological structure, evaluating the effectiveness of MSCNs involves many supply units and has more limitations on resources and other influencing factors, which makes it difficult for the traditional methods to handle it [13,21].…”

“…With the development of complex networks, the complex network technology is used to evaluate and optimize structural properties of supply chain networks while regarding them as continuous networks. However, supply chain networks are discrete networks in practice [13,15]. In effectiveness evaluation, continuous networks and discrete networks have great differences, if the attributes of the network are indiscriminate, wrong conclusions can easily be made.…”

“…But the analytical method of complex networks can solve this problem very well [12]. Some researchers consider the MSCN as a continuous and complex network to analyze the reliability and resilience of its structure [13], while few strategists study the MSCNs from the perspective of the effectiveness and efficiency evaluation of discrete networks.…”

Topological Resilience Analysis of Supply Networks under Random Disruptions and Targeted Attacks

“…Based on the complex network theory, Chen and Lin [8] study the characteristics of the complex supply chain and present an invulnerability analysis method to evaluate its robustness against random failures and deliberate assaults. Using a military logistic network as a case study (see in Figure 1 a hierarchical illustration of it, where FSB stands for forward support battalions, and MSB for main support battalions), Zhao et al [9] propose another taxonomy of resilience metrics that reflect the heterogeneous roles of different types of units in supply networks, and present a hybrid and tunable network growth model. Kim et al [10] present a comprehensive conceptualization of the supplynetwork disruption and resilience from a network structural perspective.…”

Resilience of Core-Periphery Networks in the Case of Rich-Club

“…Indeed, network performances (especially in terms of routing ability and stability) are directly related to their resilience and thus to the capabilities of networks in tolerating loss of important elements such as bridges or hubs. Mainly because of its tangible implications [8][9][10][11], resilience has been investigated across many different network structures (both synthetic and real) and there is now knowledge regarding how specific kinds of networks react to specific kinds of losses [12,13]. In more detail, since resilience is related to the ability to withstand deliberate attacks and incidents, studies about this topic have tended to consider a large variety of structural failures (both induced by attack or naturally occurring) which involve both specific (i.e., chosen by their properties like the centrality indexes) and random nodes.…”