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Indexed by:期刊论文

Date of Publication:2017-11-30

Journal:EXPERT SYSTEMS WITH APPLICATIONS

Included Journals:Scopus、SCIE、EI、SSCI

Volume:87

Page Number:56-69

ISSN No.:0957-4174

Key Words:Liquefied natural gas (LNG); Multi-objective Programming; Extreme events; Improved Simulated Annealing Algorithm; Software implementation

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. (C) 2017 Elsevier Ltd. All rights reserved.