DocumentCode :
2326148
Title :
Modeling and optimization of ocean-going unloading problem with stochastic demand
Author :
Shengkai, Jin ; Shiji, Song ; Yuli, Zhang ; Cheng, Wu
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
fYear :
2010
fDate :
10-12 April 2010
Firstpage :
658
Lastpage :
663
Abstract :
One of the important Challenges for steel enterprises is to reduce the procurement cost occurred in unloading process of ocean-going ship, ore as the main material contains usually some uncertain demand, and its unloading process is a typically complex problem with large scale. In this paper, unloading cost composition is analyzed strictly, and its mathematical model with stochastic demand is established wherein various complex constrains are considered. Further, Lagrangian relaxation algorithm and genetic algorithm combined with sub-gradient is designed to solve this problem. Finally, an example is simulated and illustrated to interpret the effectiveness and accuracy of proposed algorithm.
Keywords :
cost reduction; genetic algorithms; procurement; steel industry; unloading; Lagrangian relaxation algorithm; cost reduction; genetic algorithm; ocean-going unloading problem; optimization; procuremen¿t; steel enterprises; stochastic demand; Building materials; Costs; Genetic algorithms; Lagrangian functions; Large-scale systems; Marine vehicles; Mathematical model; Procurement; Steel; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2010 International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-6450-0
Type :
conf
DOI :
10.1109/ICNSC.2010.5461582
Filename :
5461582
Link To Document :
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