An innovative decision support tool for liquefied natural gas supply chain planning

IF 2 Q3 BUSINESS
C. Papaleonidas, D. Lyridis, A. Papakostas, D. Konstantinidis
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引用次数: 2

Abstract

Purpose The purpose of this paper is to improve the tactical planning of the stakeholders of the midstream liquefied natural gas (LNG) supply chain, using an optimisation approach. The results can contribute to enhance the proactivity on significant investment decisions. Design/methodology/approach A decision support tool (DST) is proposed to minimise the operational cost of a fleet of vessels. Mixed integer linear programming (MILP) used to perform contract assignment combined with a genetic algorithm solution are the foundations of the DST. The aforementioned methods present a formulation of the maritime transportation problem from the scope of tramp shipping companies. Findings The validation of the DST through a realistic case study illustrates its potential in generating quantitative data about the cost of the midstream LNG supply chain and the annual operations schedule for a fleet of LNG vessels. Research limitations/implications The LNG transportation scenarios included assumptions, which were required for resource reasons, such as omission of stochasticity. Notwithstanding the assumptions made, it is to the authors’ belief that the paper meets its objectives as described above. Practical implications Potential practitioners may exploit the results to make informed decisions on the operation of LNG vessels, charter rate quotes and/or redeployment of existing fleet. Originality/value The research has a novel approach as it combines the creation of practical management tool, with a comprehensive mathematical modelling, for the midstream LNG supply chain. Quantifying future fleet costs is an alternative approach, which may improve the planning procedure of a tramp shipping company.
液化天然气供应链规划的创新决策支持工具
目的本文的目的是改善中游液化天然气(LNG)供应链的利益相关者的战术规划,使用优化方法。研究结果有助于提高重大投资决策的主动性。设计/方法/方法提出了一种决策支持工具(DST),以最大限度地降低船队的运营成本。用于执行合同分配的混合整数线性规划(MILP)与遗传算法解决方案相结合是DST的基础。上述方法提出了一种从不定期船公司范围出发的海上运输问题的表述。通过一个实际的案例研究验证了DST,说明了它在生成关于中游液化天然气供应链成本和液化天然气船队年度运营计划的定量数据方面的潜力。研究局限/启示LNG运输情景包括了一些假设,这些假设是由于资源原因所必需的,例如忽略了随机性。尽管做出了假设,但作者相信本文符合上述目标。实际意义潜在的从业者可以利用这些结果对液化天然气船的运营、租船费率报价和/或现有船队的重新部署做出明智的决定。该研究采用了一种新颖的方法,因为它结合了实用管理工具的创建,以及针对中游液化天然气供应链的全面数学建模。量化未来船队成本是一种替代方法,可以改善不定期船公司的计划程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.80
自引率
0.00%
发文量
19
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