research-article

Survivability of Multiagent-Based Supply Networks: A Topological Perspective

Authors:

Hari Prasad Thadakamalla,

Usha Nandini Raghavan,

Soundar Kumara,

Albert AlbertAuthors Info & Claims

IEEE Intelligent Systems, Volume 19, Issue 5

Pages 24 - 31

https://doi.org/10.1109/MIS.2004.49

Published: 01 September 2004 Publication History

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Abstract

Real-world complex networks such as the World Wide Web and social and biological interaction networks exhibit small-world behavior and an approximately scale-free degree distribution. More importantly, many of these networks prove highly resilient and survivable to environmental changes. These complex systems' ability to survive depends largely on their topological structure. Supply networks, usually modeled as multiagent systems, can be represented as complex networks with entities as nodes and the interactions between them as edges. Taking a topological perspective and applying the principles of complex network theory can illuminate strategies to improve supply networks' survivability.

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Mu DYue X(2021)Heterogeneity and Environmental Preferences Shape the Evolution of Cooperation in Supply NetworksComplexity10.1155/2021/88948872021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/8894887
Dubey APentland ADaumé HSingh A(2020)Kernel methods for cooperative multi-agent contextual banditsProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525195(2740-2750)Online publication date: 13-Jul-2020
https://dl.acm.org/doi/10.5555/3524938.3525195
Dubey APentland ADaumé HSingh A(2020)Cooperative multi-agent bandits with heavy tailsProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525194(2730-2739)Online publication date: 13-Jul-2020
https://dl.acm.org/doi/10.5555/3524938.3525194
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Survivability of Multiagent-Based Supply Networks: A Topological Perspective
1. Mathematics of computing
  1. Discrete mathematics
    1. Graph theory
2. Theory of computation
  1. Design and analysis of algorithms
    1. Graph algorithms analysis

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Published In

IEEE Intelligent Systems Volume 19, Issue 5

September 2004

87 pages

ISSN:1541-1672

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IEEE Educational Activities Department

United States

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Published: 01 September 2004

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Mu DYue X(2021)Heterogeneity and Environmental Preferences Shape the Evolution of Cooperation in Supply NetworksComplexity10.1155/2021/88948872021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/8894887
Dubey APentland ADaumé HSingh A(2020)Kernel methods for cooperative multi-agent contextual banditsProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525195(2740-2750)Online publication date: 13-Jul-2020
https://dl.acm.org/doi/10.5555/3524938.3525195
Dubey APentland ADaumé HSingh A(2020)Cooperative multi-agent bandits with heavy tailsProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525194(2730-2739)Online publication date: 13-Jul-2020
https://dl.acm.org/doi/10.5555/3524938.3525194
Xia H(2020)Improve the Resilience of Multilayer Supply Chain NetworksComplexity10.1155/2020/65964832020Online publication date: 17-Jan-2020
https://dl.acm.org/doi/10.1155/2020/6596483
Cao ZCai ZTabak B(2020)Channel Selection Strategy for a Retailer with Finance Constraint in a Supply Chain Based on Complex Network TheoryComplexity10.1155/2020/62314272020Online publication date: 1-Jan-2020
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Lou PChen YGao S(2020)Adaptive Variable Neighborhood Search-Based Supply Network Reconfiguration for Robustness EnhancementComplexity10.1155/2020/12929382020Online publication date: 8-Dec-2020
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Brintrup AWichmann PWoodall PMcFarlane DNicks EKrechel W(2018)Predicting Hidden Links in Supply NetworksComplexity10.1155/2018/91043872018Online publication date: 1-Jan-2018
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Perera SBell MPiraveenan MKasthurirathna DParhi M(2018)Topological Structure of Manufacturing Industry Supply Chain NetworksComplexity10.1155/2018/39243612018Online publication date: 3-Oct-2018
https://dl.acm.org/doi/10.1155/2018/3924361
Xiong BLi BFan RZhou QLi W(2017)Modeling and Simulation for Effectiveness Evaluation of Dynamic Discrete Military Supply Chain NetworksComplexity10.1155/2017/60520372017Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.1155/2017/6052037
Zhang YDuan HGeng Z(2017)Evolutionary Mechanism of Frangibility in Social Consensus System Based on Negative Emotions SpreadComplexity10.1155/2017/40370492017Online publication date: 28-Jun-2017
https://dl.acm.org/doi/10.1155/2017/4037049
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Multiagent Simulation of Complex Dynamic Evolving Network's Survivability

A Multiagent Systems Perspective on Industry 4.0 Supply Networks

Structural investigation of supply networks: A social network analysis approach

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