Liquefied natural gas importing security strategy considering multi-factor: A multi-objective programming approach. (30th November 2017)

• Record Type: Journal Article
• Authors: Zhang, Xiao-Nan; Zhong, Qiu-Yan; Qu, Yi; Li, Hong-Lei
• Is Part Of: Expert systems with applications. Volume 87(2017)
• Page Start: 56
• Page End: 69
• Publication Date: 2017-11-30
• Subjects: Liquefied natural gas (LNG ) -- Multi-objective Programming -- Extreme events -- Improved Simulated Annealing Algorithm -- Software implementation; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2017.05.077
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: The multi-objective programming model for LNG importing is established. This model connects emergency management with LNG-importing programming. Decision preferences and extreme events have a great influence on LNG importing. Abstract: LNG importing strategies, in the literature, are primarily studied under a common single-factor framework. However, LNG importing strategies are affected by a variety of factors. To address this existing gap, this paper proposes a Multi-Objective Programming model, which takes into account the cost, the country risk, the shipping risk, and the impact of extreme events. A pure structural change model is used to determine the risk impact coefficient for extreme events. An enhanced Simulated Annealing Algorithm is then used to solve the LNG-importing optimization problem. An experimental study is further conducted to verify the practicability of the proposed approach in the case of China's LNG-importing data. The software implementation of the proposed model is developed in Python. The proposed model provides a decision support tool for LNG importing companies to find an efficient portfolio strategy for LNG importing. The optimization model can be used for analyzing similar scenarios involving such dimensions as economy, energy security, and especially energy diversification.