Wednesday, September 21, 2022

Mitigation of Supply Chain Disruptions by Criminal Agents

Since the outbreak of COVID, the role of supply chains has been brought front and center in many aspects of our daily lives. For example, the disruption to supply chains can significantly influence the operation of the world economy and this has been shown to permeate and affect a large majority of countries and their citizens. However, it is not just diseases outbreaks that can affect them, but also criminal agents. To this end at the 15th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (or SBP-BRiMs for short), Abhisekh Rana, Hamdi Kavak, Sean Luke, Carlotta DomeniconiJim Jones and myself have a paper entitled "Mitigation of Optimized Pharmaceutical Supply Chain Disruptions by Criminal Agents."

The paper presents some initial results from a model that explores the disruptions to supply chains by a criminal agent and possible mitigation strategies. We construct a model of a typical pharmaceutical manufacturing supply chain, which is implemented via discrete event simulation. The criminal agent optimizes its resource allocation using a CMA-ES algorithm to maximize disruption to the supply chain. CMA-ES is part of a family of sample-based optimization techniques collectively known as evolutionary algorithms.  Broadly speaking, CMA-ES starts with a sample of random candidate solutions to optimize.  It then iteratively assesses the quality of each candidate solution, then performs resampling based on their quality to produce a new sample of candidates. By combining our supply chain model with our criminal agent, and by leveraging CMA-ES, we attempt to identify the main bottlenecks and the most vulnerable points in the pharmaceutical supply chain. Our findings show criminal agents can cause cascading damage and exploit vulnerabilities, which inherently exist within the supply chain itself. We also demonstrate how basic mitigation strategies can efficaciously alleviate this potential damage.  If this sounds of interest, below we provide the abstract to the paper, along with some of the key figures and at the bottom of the post the full reference and a link to the paper.

Abstract: 

Disruption to supply chains can significantly influence the operation of the world economy and this has been shown to permeate and affect a large majority of countries and their citizens. We present initial results from a model that explores the disruptions to supply chains by a criminal agent and possible mitigation strategies. We construct a model of a typical pharmaceutical manufacturing supply chain, which is implemented via discrete event simulation. The criminal agent optimizes its resource allocation to maximize disruption to the supply chain. Our findings show criminal agents can cause cascading damage and exploit vulnerabilities, which inherently exist within the supply chain itself. We also demonstrate how basic mitigation strategies can efficaciously alleviate this potential damage. 

Keywords: Pharmaceutical supply chains, Criminal agents, Evolutionary computation, Mitigation.

A simplified version of a typical pharmaceutical supply chain.

Design of the criminal agent.
Sample simulations for the baseline model, without any disruption, and attacks at the five main disruption points in the supply chain.

Summary statistics and sample simulations for CMAES optimized disruptions with and without mitigation in place.

Full Reference:

Rana, R., Kavak, H., Crooks, A.T., Domeniconi, C., Luke, S. and Jones, J. (2022), Mitigation of Optimized Pharmaceutical Supply Chain Disruptions by Criminal Agents, in Thomson, R., Dancy, C. and Pyke, P. (eds), Proceedings of the 2022 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation, Pittsburgh, PA., pp 13-23. (pdf)

 

Monday, September 19, 2022

Information propagation on cyber, relational and physical spaces about covid-19 vaccine

It seems that its been a quite some time that we posted about geosocial analysis but in a recent paper with  Fuzhen Yin  and Li Yin entitled "Information Propagation on Cyber, Relational and Physical Spaces about Covid-19 Vaccine: Using Social Media and the Splatial Framework" published in Computers, Environment and Urban Systems we revisit this line of work while at the same time linking it to Covid and vaccination debates. 

Specifically we examine the interaction between cyber, relational (i.e, networks between objects), and physical spaces using the Splatial framework. Through our analysis focused on New York State, we find that non-polarized vaccination debates were observed in cyber, relational, and physical spaces. Furthermore,  we found that while physical space users had less anti-vaccine stance than relational and cyber space users there were strong interactions are observed between physical–relational, and relational-cyber spaces.If this sort of thing interests you. Below we provide the abstract to the paper along with some figures which show the study area, our methodology and some of the results. While at the bottom of the post we provide the full reference and the link to the paper.

Abstract:

With the advent of social media, human dynamics studied in purely physical space have been extended to that of a cyber and relational context. However, connections and interactions between these hybrid spaces have not been sufficiently investigated. The “space-place (Splatial)” framework proposed in recent years allows capturing human activities in the hybrid of spaces. This study applies the Splatial framework to examine the information propagation between cyber, relational, and physical spaces through a case study of Covid-19 vaccine debates in New York State (NYS). Whereby the physical space represents the regional boundaries and locations of social media (i.e., Twitter) users in NYS, the relational space indicates the social networks of these NYS users, and the cyber space captures the larger conversational context of the vaccination debate. Our results suggest that the Covid-19 vaccine debate is not polarized across all three spaces as compared to that of other vaccines. However, the rate of users with a pro-vaccine stance decreases from physical to relational and cyber spaces. We also found that while users from different spaces interact with each other, they also engage in local communications with users from the same region or same space, and distance-based and boundary-confined clusters exist in cyber and relational space communities. These results based on the Splatial framework not only shed light on the vaccination debates but also help to define and elucidate the relationships between the three spaces. The intense interactions between spaces suggest incorporating people’s relational network and cyber presence in physical place-making.

Keywords: Covid-19, Vaccination, Social media, Social network analysis, Community detection, Urban informatics
Schematic representation of the three spaces: cyber, relational and physical spaces.

Map of study area (NYS) with the primary road system. Red dots denote collected vaccine-related tweets in NYS.

Research workflow to investigate the propagation of different opinions between three spaces: cyber, relational and physical spaces.

Network visualization of the eight top large communities in relational space. (A) Visualization of communities using ForceAtlas layout. (B) Project communities into physical space. Nodes without location information are placed outside of NYS.

The hybrid space network shows the information propagation between physical and relational spaces. (A) shows the network of all tweets, (B) shows the pro-vaccine tweets, and (C) shows the anti-vaccine tweets.
 
Full Reference:

Yin, F., Crooks, A.T. and Yin, L. (2022), Information Propagation on Cyber, Relational and Physical Spaces about Covid-19 Vaccine: Using Social Media and the Splatial Framework, Computers, Environment and Urban Systems. Available at: https://doi.org/10.1016/j.compenvurbsys.2022.101887.  (pdf)