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Systematic review reveals widespread reliance on simplified deterministic models for LNG delivery plans, highlighting the need for simulation-based optimization under operational uncertainty.
Background: The demand for natural gas and advancements in LNG technologies have made it easier and more cost-effective to transport large quantities of natural gas over long distances by cooling it and then delivering it to customers according to an annual delivery plan (ADP). This plan is crucial for the LNG supply chain to minimize operational costs and meet contractual obligations; however, there are random factors that deviate from the ADP’s initial plan, such as production rate interruptions, weather conditions, and a reduction in the number of berths. Methods: Available optimization methods for ADPs in the literature were reviewed using a systematic literature review (SLR) and validated with the PRISMA 2020 Statement checklist and flow diagram, which showed that many existing studies use simplified deterministic models to optimize ADPs within reasonable time and effort. This research suggests establishing a simulation-based optimization (sim-heuristics) framework to develop ADPs with an objective function that minimizes expected total costs while capturing real-life uncertainties. This approach will provide tactical insights to decision-makers and is adaptable for various operational policy evaluations. Conclusions: This simulation-based optimization approach could offer the LNG industry a powerful analytical engine for robust, real-world decision-making, bridging the gap between theoretical planning and operational complexity.
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Jurf et al. (2026) studied this question.
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