DocumentCode
1954598
Title
Notice of Retraction
A stochastic model and algorithm for the facility location problem
Author
Fangguo He ; Kuobin Dai
Author_Institution
Coll. of Math. & Inf. Sci., Huanggang Normal Univ., Huanggang, China
Volume
7
fYear
2010
fDate
9-11 July 2010
Firstpage
359
Lastpage
362
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The facility location problems have been applied extensively in practice. We describe a facility location problem with stochastic demand based chance-constrained programming model, and formulate an approach to conversion of the chance constraints to their respective deterministic equivalents. A Lagrangian relaxation approach using subgradient algorithm is adopted and designed for the equivalent model. The performance of the proposed method is tested by a numerical experiment, and show the effectiveness of the proposed algorithm.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The facility location problems have been applied extensively in practice. We describe a facility location problem with stochastic demand based chance-constrained programming model, and formulate an approach to conversion of the chance constraints to their respective deterministic equivalents. A Lagrangian relaxation approach using subgradient algorithm is adopted and designed for the equivalent model. The performance of the proposed method is tested by a numerical experiment, and show the effectiveness of the proposed algorithm.
Keywords
facility location; stochastic processes; Lagrangian relaxation; chance constrained programming model; deterministic equivalent; facility location; stochastic demand; stochastic model; Facility location problem; Lagrangian relaxation; Stochastic optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5564869
Filename
5564869
Link To Document