OPTIMIZING MARITIME PREPOSITIONING FORCE SELECTION OF SHIP CLASS TO RESPOND TO HUMANITARIAN ASSISTANCE AND DISASTER RELIEF OPERATIONS IN THE PACIFIC THEATER
Mclean, Gary D., Jr.
Apte, Aruna U.
Seagren, Chad W.
MetadataShow full item record
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.
Approved for public release. distribution is unlimited
Showing items related by title, author, creator and subject.
MacKenzie, Cameron A.; Apte, Aruna (Emerald Group Publishing Limited, 2016-07-27);Purpose-The purpose of this paper is to quantify elements that make fresh produce supply chains vulnerable to disruptions and to quantify the benefits of different disruption management strategies. Design/methodolog ...
Manbir Sodhi; James Ferguson; Marie Bussiere; Betty Jester (2011-04-30); NPS-AM-11-C8P25R01-080Although uncertainty in production and inventory systems is not desirable, predictions for demand are inherently uncertain. When the set of products is complex, that is, composed of multiple subassemblies, and there are ...
Beall, Ryan G. (Monterey, California: Naval Postgraduate School, 2017-06);As the demand for Unmanned Aerial System (UAS) technology increases, the current guidance, navigation, and control (GNC) algorithms will scale poorly to meet the demand because currently, significant resources are required ...