EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics

Vikas K. Garg; N. Viswanadham

doi:10.1007/978-3-642-17298-4_76

EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics

Vikas K. Garg, N. Viswanadham

Not published at Aalto University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

A global supply chain spans several regions and countries across the globe. A tremendous spurt in the extent of globalization has necessitated the need for modeling global supply chains in place of the conventional supply chains. In this paper, we propose a framework, EcoSupply, to analyze the supply chain ecosystem in a probabilistic setting unlike the existing methodologies, which presume a deterministic context. EcoSupply keeps track of the previous observations in order to facilitate improved prediction about the influence of uncertainties in the ecosystem, and provides a coherent mathematical exposition to construe the new associations, among the different supply chain stakeholders, in place of the existing links. To the best of our knowledge, EcoSupply is the first machine learning based paradigm to incorporate the dynamics of global supply chains.

Original language	English
Title of host publication	Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings
Pages	677-686
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-17298-4_76
Publication status	Published - 2010
MoE publication type	A4 Article in a conference publication
Event	International Conference on Simulated Evolution and Learning - Kanpur, India Duration: 1 Dec 2010 → 4 Dec 2010 Conference number: 8

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6457 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Simulated Evolution and Learning
Abbreviated title	SEAL
Country/Territory	India
City	Kanpur
Period	01/12/2010 → 04/12/2010

Keywords

Global Sourcing
Machine Learning
Supply Chains

Access to Document

10.1007/978-3-642-17298-4_76

OpenUrl availability

Full text

Cite this

Garg, V. K., & Viswanadham, N. (2010). EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics. In Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings (pp. 677-686). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6457 LNCS). https://doi.org/10.1007/978-3-642-17298-4_76

Garg, Vikas K. ; Viswanadham, N. / EcoSupply : A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics. Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings. 2010. pp. 677-686 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{a0722813ad0f4d81b3797d97ed062e2f,

title = "EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics",

abstract = "A global supply chain spans several regions and countries across the globe. A tremendous spurt in the extent of globalization has necessitated the need for modeling global supply chains in place of the conventional supply chains. In this paper, we propose a framework, EcoSupply, to analyze the supply chain ecosystem in a probabilistic setting unlike the existing methodologies, which presume a deterministic context. EcoSupply keeps track of the previous observations in order to facilitate improved prediction about the influence of uncertainties in the ecosystem, and provides a coherent mathematical exposition to construe the new associations, among the different supply chain stakeholders, in place of the existing links. To the best of our knowledge, EcoSupply is the first machine learning based paradigm to incorporate the dynamics of global supply chains.",

keywords = "Global Sourcing, Machine Learning, Supply Chains",

author = "Garg, {Vikas K.} and N. Viswanadham",

year = "2010",

doi = "10.1007/978-3-642-17298-4_76",

language = "English",

isbn = "3642172970",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "677--686",

booktitle = "Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings",

note = "International Conference on Simulated Evolution and Learning, SEAL ; Conference date: 01-12-2010 Through 04-12-2010",

}

Garg, VK & Viswanadham, N 2010, EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics. in Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6457 LNCS, pp. 677-686, International Conference on Simulated Evolution and Learning, Kanpur, India, 01/12/2010. https://doi.org/10.1007/978-3-642-17298-4_76

EcoSupply : A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics. / Garg, Vikas K.; Viswanadham, N.

Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings. 2010. p. 677-686 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6457 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - EcoSupply

T2 - International Conference on Simulated Evolution and Learning

AU - Garg, Vikas K.

AU - Viswanadham, N.

N1 - Conference code: 8

PY - 2010

Y1 - 2010

N2 - A global supply chain spans several regions and countries across the globe. A tremendous spurt in the extent of globalization has necessitated the need for modeling global supply chains in place of the conventional supply chains. In this paper, we propose a framework, EcoSupply, to analyze the supply chain ecosystem in a probabilistic setting unlike the existing methodologies, which presume a deterministic context. EcoSupply keeps track of the previous observations in order to facilitate improved prediction about the influence of uncertainties in the ecosystem, and provides a coherent mathematical exposition to construe the new associations, among the different supply chain stakeholders, in place of the existing links. To the best of our knowledge, EcoSupply is the first machine learning based paradigm to incorporate the dynamics of global supply chains.

AB - A global supply chain spans several regions and countries across the globe. A tremendous spurt in the extent of globalization has necessitated the need for modeling global supply chains in place of the conventional supply chains. In this paper, we propose a framework, EcoSupply, to analyze the supply chain ecosystem in a probabilistic setting unlike the existing methodologies, which presume a deterministic context. EcoSupply keeps track of the previous observations in order to facilitate improved prediction about the influence of uncertainties in the ecosystem, and provides a coherent mathematical exposition to construe the new associations, among the different supply chain stakeholders, in place of the existing links. To the best of our knowledge, EcoSupply is the first machine learning based paradigm to incorporate the dynamics of global supply chains.

KW - Global Sourcing

KW - Machine Learning

KW - Supply Chains

UR - http://www.scopus.com/inward/record.url?scp=78650734998&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-17298-4_76

DO - 10.1007/978-3-642-17298-4_76

M3 - Conference contribution

AN - SCOPUS:78650734998

SN - 3642172970

SN - 9783642172977

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 677

EP - 686

BT - Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings

Y2 - 1 December 2010 through 4 December 2010

ER -

Garg VK, Viswanadham N. EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics. In Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings. 2010. p. 677-686. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-17298-4_76

EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics

Abstract

Publication series

Conference

Keywords

Access to Document

OpenUrl availability

Other files and links

Fingerprint

Cite this