Abstract

Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers. We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

Original languageEnglish (US)
Article number063029
JournalNew Journal of Physics
Volume17
Issue number6
DOIs
StatePublished - Jun 23 2015

Fingerprint

resilience
optimization
resources
system failures
fixing
traffic
actuators
grids
routes
perturbation
requirements
expansion

Keywords

  • cascading failure
  • optimization
  • resilience
  • supply-demand networks

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Optimization and resilience of complex supply-demand networks. / Zhang, Si Ping; Huang, Zi Gang; Dong, Jia Qi; Eisenberg, Daniel; Seager, Thomas; Lai, Ying-Cheng.

In: New Journal of Physics, Vol. 17, No. 6, 063029, 23.06.2015.

Research output: Contribution to journalArticle

Zhang, Si Ping ; Huang, Zi Gang ; Dong, Jia Qi ; Eisenberg, Daniel ; Seager, Thomas ; Lai, Ying-Cheng. / Optimization and resilience of complex supply-demand networks. In: New Journal of Physics. 2015 ; Vol. 17, No. 6.
@article{3bc9b18538f94369b63a9a3732578483,
title = "Optimization and resilience of complex supply-demand networks",
abstract = "Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers. We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.",
keywords = "cascading failure, optimization, resilience, supply-demand networks",
author = "Zhang, {Si Ping} and Huang, {Zi Gang} and Dong, {Jia Qi} and Daniel Eisenberg and Thomas Seager and Ying-Cheng Lai",
year = "2015",
month = "6",
day = "23",
doi = "10.1088/1367-2630/17/6/063029",
language = "English (US)",
volume = "17",
journal = "New Journal of Physics",
issn = "1367-2630",
publisher = "IOP Publishing Ltd.",
number = "6",

}

TY - JOUR

T1 - Optimization and resilience of complex supply-demand networks

AU - Zhang, Si Ping

AU - Huang, Zi Gang

AU - Dong, Jia Qi

AU - Eisenberg, Daniel

AU - Seager, Thomas

AU - Lai, Ying-Cheng

PY - 2015/6/23

Y1 - 2015/6/23

N2 - Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers. We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

AB - Supply-demand processes take place on a large variety of real-world networked systems ranging from power grids and the internet to social networking and urban systems. In a modern infrastructure, supply-demand systems are constantly expanding, leading to constant increase in load requirement for resources and consequently, to problems such as low efficiency, resource scarcity, and partial system failures. Under certain conditions global catastrophe on the scale of the whole system can occur through the dynamical process of cascading failures. We investigate optimization and resilience of time-varying supply-demand systems by constructing network models of such systems, where resources are transported from the supplier sites to users through various links. Here by optimization we mean minimization of the maximum load on links, and system resilience can be characterized using the cascading failure size of users who fail to connect with suppliers. We consider two representative classes of supply schemes: load driven supply and fix fraction supply. Our findings are: (1) optimized systems are more robust since relatively smaller cascading failures occur when triggered by external perturbation to the links; (2) a large fraction of links can be free of load if resources are directed to transport through the shortest paths; (3) redundant links in the performance of the system can help to reroute the traffic but may undesirably transmit and enlarge the failure size of the system; (4) the patterns of cascading failures depend strongly upon the capacity of links; (5) the specific location of the trigger determines the specific route of cascading failure, but has little effect on the final cascading size; (6) system expansion typically reduces the efficiency; and (7) when the locations of the suppliers are optimized over a long expanding period, fewer suppliers are required. These results hold for heterogeneous networks in general, providing insights into designing optimal and resilient complex supply-demand systems that expand constantly in time.

KW - cascading failure

KW - optimization

KW - resilience

KW - supply-demand networks

UR - http://www.scopus.com/inward/record.url?scp=84938635217&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84938635217&partnerID=8YFLogxK

U2 - 10.1088/1367-2630/17/6/063029

DO - 10.1088/1367-2630/17/6/063029

M3 - Article

AN - SCOPUS:84938635217

VL - 17

JO - New Journal of Physics

JF - New Journal of Physics

SN - 1367-2630

IS - 6

M1 - 063029

ER -