DocumentCode
1903221
Title
Optimization on Safety Thickness of Roof for Mining Based on Genetic Algorithm
Author
Shi, Xiuzhi ; Gao, Feng
Author_Institution
Sch. of Resources & Safety Eng., Central South Univ., Changsha, China
Volume
3
fYear
2009
fDate
10-11 Oct. 2009
Firstpage
234
Lastpage
237
Abstract
According to optimization on safety thickness of roof for underground mining, which is a complex problem affected by multiple factors. On the basis of Genetic Algorithm (GA), each influencing factor on safety thickness of roof is considered as different gene and used to express individual composition factor of population. Therefore, each arbitrary group composed by different influencing factors can be used as a population. Then, by constructing objective function, designing optimization variables and determining constraint condition, the mathematical model of optimization on safety thickness of roof can be constructed. By using the Evolver software, which is based on the thought of GA, the optimization on safety thickness of roof for stopping the orebody No.92, under the overlap zones in Tongkeng Mine, is studied. The optimized results show that more conformable and accurate of the safety thickness of roof compared with the results obtained by numerical simulation and mathematical prediction.
Keywords
genetic algorithms; mechanical engineering computing; mining; roofs; safety; Evolver software; Tongkeng Mine; genetic algorithm; objective function; orebody No 92; roof safety thickness; underground mining; Automation; Constraint optimization; Design optimization; Encoding; Evolution (biology); Genetic algorithms; Genetic engineering; Mathematical model; Numerical simulation; Software safety; Evolver; Genetic Algorithm; Optimization; safety thickness of roof;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location
Changsha, Hunan
Print_ISBN
978-0-7695-3804-4
Type
conf
DOI
10.1109/ICICTA.2009.523
Filename
5287944
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