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Pricing Strategy Research of Lng Based on Monte-Carlo Simulation and Genetic Algorithms

Author: OuZuoQi
Tutor: XieZuoLing
School: Harbin Institute of Technology
Course: Business management
Keywords: LNG Pricing Strategy Monte-Carlo Simulation Genetic Algorithms
CLC: F416.22
Type: Master's thesis
Year: 2010
Downloads: 93
Quote: 0
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Abstract


According to International Energy Agency (IEA), natural gas will be of greater advantage than oil and coal in the 21st century. However for making-up the demand gap of our country, it is determined to make the liquified natural gas (LNG) project practice. And a scientific pricing stratege is a very important factor for ensuring the project’s security. But the discussion on this topic is not much. It is difficult to guide the LNG enterprise to make a proper price. Therefore under the operating model of our country, to make a reasonable LNG pricing strategy is an urgent task.This thesis is focused on research into the pricing strategy of LNG under such a background. First, the pricing mechanism of LNG is introduced, including well pricing mechanism and transformation fee mechanism. Then by combining with the reality of our country, an analysis of the fee rate design of LNG is made. And Monte-Carlo simulation (MC) and Genetic Algorithms (GA) are choosed as tools in recognition of the problem’s complication and the limitation of traditional research methods. Following that, the decision model, which is based on previous research, is established for solving fee rate coefficient decision problem and pricing problem. The theoritical models are made in EXCEL and then @RISK is used to make the Monte-Carlo simulation and GA calculation. At last, the decision model and the simulating model are both applied to a case, proving the validity of the model.This research also offers a decisiong method for solving LNG pricing problems or in the pricing of similar monopolies.

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CLC: > Economic > Industrial economy > The world's industrial economy > Industrial sector economy > Energy industry,power industry > Oil and gas industry
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