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Strategic Analytical Solving Hueristic for Supply and Force Flow Logistics
Abstract
Humanitarian catastrophes, such as hurricane landfalls, volcanic eruptions, earthquakes, can be exacerbated by supply chain concerns that impede relief efforts. Using several small data structures to complete and analyze courses of action for large-scale supply chain problems is a novel method for solving logistical problems. In high-fidelity modeling, it is challenging to capture real-time adjustments to supply chain actions Prior research has addressed the deficiencies and simulation of logistical issues for real-world applications but has lacked the ability to fit within the operational context. In the realm of research, there has been little consideration of time constraints. In this paper, we dissect the novel method of coupling operational planning with a quick-turn physics-based model using a deterministic approach to manipulating variables. This provides the planning team and leadership with a more sophisticated analytical approach and a shorter delay in solution exploration based on planning factors. We approached this issue using an output file and scenario development based on a data structure developed by the logistical branches of the III Marine expeditionary forces cell. We discovered that, for the first time, a model could be used in real-time planning to provide leadership with an analytically supported decision-making process, whereas previously the approach was entirely qualitative and based on large assumptions or a 90-day optimization that only influenced research projects.
Citation
McReynolds, Ezekiel Joseph (2023). Strategic Analytical Solving Hueristic for Supply and Force Flow Logistics. Master's thesis, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /198827.