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

Ei julkaistu Aalto-yliopiston affiliaatiolla

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

1 Sitaatiot (Scopus)

Abstrakti

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.

Alkuperäiskieli	Englanti
Otsikko	Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings
Sivut	677-686
Sivumäärä	10
DOI - pysyväislinkit	https://doi.org/10.1007/978-3-642-17298-4_76
Tila	Julkaistu - 2010
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	International Conference on Simulated Evolution and Learning - Kanpur, Intia Kesto: 1 jouluk. 2010 → 4 jouluk. 2010 Konferenssinumero: 8

Julkaisusarja

Nimi	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vuosikerta	6457 LNCS
ISSN (painettu)	0302-9743
ISSN (elektroninen)	1611-3349

Conference

Conference	International Conference on Simulated Evolution and Learning
Lyhennettä	SEAL
Maa/Alue	Intia
Kaupunki	Kanpur
Ajanjakso	01/12/2010 → 04/12/2010

Pääsy asiakirjaan

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

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Link to publication in Scopus

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

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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",

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Garg, VK & Viswanadham, N 2010, EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics. julkaisussa 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), Vuosikerta 6457 LNCS, Sivut 677-686, International Conference on Simulated Evolution and Learning, Kanpur, Intia, 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. s. 677-686 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vuosikerta 6457 LNCS).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

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T1 - EcoSupply

T2 - International Conference on Simulated Evolution and Learning

AU - Garg, Vikas K.

AU - Viswanadham, N.

N1 - Conference code: 8

PY - 2010

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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

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SN - 3642172970

SN - 9783642172977

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

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Garg VK, Viswanadham N. EcoSupply: A machine learning framework for analyzing the impact of ecosystem on global supply chain dynamics. julkaisussa Simulated Evolution and Learning - 8th International Conference, SEAL 2010, Proceedings. 2010. s. 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

Abstrakti

Julkaisusarja

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