DocumentCode :
2670302
Title :
Genetic Algorithm optimizer for blend planning
Author :
Xiaoqiang, Zhao ; Weirong, Liu ; Jun, Wang
Author_Institution :
Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou
fYear :
2008
fDate :
16-18 July 2008
Firstpage :
86
Lastpage :
88
Abstract :
Process plant operations planning optimization is a difficult real life problem because it is non-linear, and mixes continuous and discrete variables. These mixed variable problems canpsilat be handled by conventional mathematical optimization techniques without a great deal of effort and operations research knowledge. Genetic algorithms (GA) is a popular artificial intelligence based optimization techniques. It is easy to use, handles mixed integers, strongly non-linear problems, and quickly finds the global optimum of a problem. So the GA optimizer can solve blend planning problem with non-linear.
Keywords :
artificial intelligence; blending; fuel processing industries; genetic algorithms; process planning; artificial intelligence based optimization techniques; blend planning; conventional mathematical optimization techniques; genetic algorithm optimizer; process plant operations planning optimization; Genetic algorithms; Integer linear programming; Neural networks; Operations research; Optimization methods; Organisms; Petroleum; Process planning; Quadratic programming; Technology planning; Blend planning; Genetic algorithm; Optimizer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
Type :
conf
DOI :
10.1109/CHICC.2008.4605751
Filename :
4605751
Link To Document :
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