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Optimizing Maritime Prepositioning Force Selection of Ship Class to Respond to Humanitarian Assistance And Disaster Relief Operations In The Pacific Theater.
| 题名： | Optimizing Maritime Prepositioning Force Selection of Ship Class to Respond to Humanitarian Assistance And Disaster Relief Operations In The Pacific Theater. |
| 作者： | Mclean, G. J. D.; Burgos, A. |
| 关键词： | Humanitarian assistance, Ships, Military operations, Task forces, Natural disasters, Supply chain, Disaster management, Marine corps, Transportation, Hadr(humanitarian assistance and disaster relief), Iii mef, Optimization model, Mpf(maritime prepositioning force), Logistics chain, Jtop-s(joint transportation optimization planner sealift) |
| 摘要： | This project will focus on analyzing critical planning factors of the different ship classes within the Maritime Prepositioning Force (MPF) program for Humanitarian Assistance and Disaster Relief (HADR) operations in the Pacific theater. By optimizing how gear is transported, Marines can provide relief in an expedient manner and minimize cost (i.e., loss of life) in a HADR. We develop an initial response model, Joint Transportation Optimization Planner Sealift (JTOP-S), to optimize the size and number of ships needed to conduct HADR effectively and efficiently based on the equipment utilized. The port functionality, capacity of the ships, and supply and demand requirements are some constraints that hinder the aid given and delay the process. JTOP-S is able to determine an optimal solution, given the different inputs and parameters. The scenarios we ran to test the model resulted in the following findings: (1) Capacity of the different ship classes is not a limiting factor, the speed is. (2) The model will first max out the available supplies from the closest Sea Port of Embarkation (SPOE)to the Sea Port of Debarkation (SPOD) via the fastest mode of transport. (3) The model will then select the ship class that has the lowest planning factor average from the same SPOE. (4) If the demand is not met from one SPOE, the model will source the remaining demand from the next closest SPOE via the fastest mode of transportation, and then from the planning factor average value. |
| 报告类型： | 科技报告 |
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