An on-line probabilistic paradigm for optimal disassembly planning

Ying Tang; Peter Renner

doi:10.1109/SOLI.2006.235396

An on-line probabilistic paradigm for optimal disassembly planning

Ying Tang, Peter Renner

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

Disassembly is of growing importance in material and product recovery. However, the deployment of this process is complicated due to the lack of a priori information necessary for its control and planning. This paper develops a predictive model to tackle this problem.

Original language	English (US)
Title of host publication	2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006
Pages	770-774
Number of pages	5
DOIs	https://doi.org/10.1109/SOLI.2006.235396
State	Published - 2006
Event	2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006 - Shanghai, China Duration: Jun 21 2006 → Jun 23 2006

Publication series

Name	2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006

Other

Other	2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006
Country/Territory	China
City	Shanghai
Period	6/21/06 → 6/23/06

All Science Journal Classification (ASJC) codes

Information Systems
Information Systems and Management

Access to Document

10.1109/SOLI.2006.235396

Cite this

Tang, Y., & Renner, P. (2006). An on-line probabilistic paradigm for optimal disassembly planning. In 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006 (pp. 770-774). Article 1700965 (2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006). https://doi.org/10.1109/SOLI.2006.235396

@inproceedings{fa368a01fe694b6f92f580b0dc45f7cb,

title = "An on-line probabilistic paradigm for optimal disassembly planning",

abstract = "Disassembly is of growing importance in material and product recovery. However, the deployment of this process is complicated due to the lack of a priori information necessary for its control and planning. This paper develops a predictive model to tackle this problem.",

author = "Ying Tang and Peter Renner",

year = "2006",

doi = "10.1109/SOLI.2006.235396",

language = "English (US)",

isbn = "1424403189",

series = "2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006",

pages = "770--774",

booktitle = "2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006",

note = "2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006 ; Conference date: 21-06-2006 Through 23-06-2006",

}

Tang, Y & Renner, P 2006, An on-line probabilistic paradigm for optimal disassembly planning. in 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006., 1700965, 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006, pp. 770-774, 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006, Shanghai, China, 6/21/06. https://doi.org/10.1109/SOLI.2006.235396

An on-line probabilistic paradigm for optimal disassembly planning. / Tang, Ying; Renner, Peter.
2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006. 2006. p. 770-774 1700965 (2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

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AU - Renner, Peter

PY - 2006

Y1 - 2006

N2 - Disassembly is of growing importance in material and product recovery. However, the deployment of this process is complicated due to the lack of a priori information necessary for its control and planning. This paper develops a predictive model to tackle this problem.

AB - Disassembly is of growing importance in material and product recovery. However, the deployment of this process is complicated due to the lack of a priori information necessary for its control and planning. This paper develops a predictive model to tackle this problem.

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DO - 10.1109/SOLI.2006.235396

M3 - Conference contribution

AN - SCOPUS:36049008788

SN - 1424403189

SN - 9781424403189

T3 - 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006

SP - 770

EP - 774

BT - 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006

T2 - 2006 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2006

Y2 - 21 June 2006 through 23 June 2006

ER -

An on-line probabilistic paradigm for optimal disassembly planning

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