DocumentCode :
620244
Title :
Mathematical model and algorithm of optimal resource allocation in the large iron & steel complex
Author :
Deng Pan ; Yingping Zheng
Author_Institution :
Sch. of Electron. & Inf. Eng., Tongji Univ., Shanghai, China
fYear :
2013
fDate :
25-27 May 2013
Firstpage :
3074
Lastpage :
3079
Abstract :
The reduction-producing is an important means of energy saving and emission reduction. For this purpose, the augmented vector is used to describe the inputs/outputs of every process in the large iron & steel complex, and then the optimal resource allocation is studied under the conditions of current equipment, technology and the operational level, the mathematical model is constructed to find an optimal resource allocation scheme for every process. The genetic algorithm is used to simulate the resource allocation of the large iron & steel complex, and determine the optimal resource allocation scheme. The taken measures include the reduction of the purchased materials, the full utilization of the recycled materials and the reasonable allocation of the input and output materials of every process. The simulation shows the validity of the mathematical mode and its algorithm. The purpose of energy saving and emission reduction can be achieved to some extent.
Keywords :
air pollution; energy conservation; genetic algorithms; purchasing; recycling; resource allocation; steel industry; augmented vector; emission reduction; energy saving; genetic algorithm; iron&steel complex; material recycling; mathematical algorithm; mathematical model; optimal resource allocation scheme; purchased material reduction; reduction-producing; resource allocation simulation; Iron; Materials; Mathematical model; Production; Resource management; Steel; Vectors; Algorithm; Large Iron & Steel Complex; Mathematical Model; Optimal Resource Allocation; Reduction-producing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
Type :
conf
DOI :
10.1109/CCDC.2013.6561473
Filename :
6561473
Link To Document :
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