6,429 research outputs found
Optimal Deployment and Employment of Naval Air Connectors
No full textThe Navy Air Logistics Office (NALO) is tasked with supporting fleet operations and readiness. They accomplish this through planning air cargo and passenger transport missions that fulfill demands around the world. These missions are executed by the Fleet Logistics Support Wing (FLSW), which is a U.S. Navy Reserve wing stationed at Naval Air Station Joint Reserve Base Fort Worth, Texas. FSLW comprises 11 transportation squadrons spread over 10 bases in different locations in the continental U.S. and Hawaii. Based on aircargo demand data provided by the sponsor, we have analyzed the FLSW’s current operational practices and squadron allocation, with the objective of identifying potential improvements in operations and deployment (i.e., re-allocation). We have addressed two main questions: (1) Given the current deployment of aircraft in bases, can we improve the employment of aircraft, that is, the assignment of aircraft from bases to missions? (2) Can we improve the deployment of aircraft, that is, the allocation of aircraft to bases? We have developed two variants of a mixed-integer program (MIP) that address these two questions. One variant is called employment model, and the other is called deployment model. The employment model, which optimizes assignments of aircraft to missions, is run twice: once with respect to the current FLSW deployment of aircraft, and once with respect to a redeployment of aircraft in bases, which results from running the deployment optimization model. With these models, we identify inefficiencies in the current operations and propose directions for improvement.Approved for public release; distribution is unlimited.This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Naval Postgraduate School, Naval Research ProgramOPNAV N98 – Air Warfar
Comparison of Operational Availability and Endurance Supply Metrics for Naval Aviation Readiness-Based Sparing
No full textNPS NRP Executive SummaryNaval Supply Systems Command (NAVSUP), Weapons System Support, is the U.S. Navy organization that provides naval assets with supply support for their weapon systems (WS). One of the most complex problems that NAVSUP planners face is making readiness-based sparing allowancing decisions, which involve afloat units (such as aircraft carries or amphibious ships), and ashore sites (such as naval air stations). We focus on allowancing for naval aviation WS. One of the goals is to find a proper balance between fleet “readiness” and allowancing cost. While the latter can be easily quantified, readiness is a more complex concept. Currently, NAVSUP uses a metric called operational availability (Ao) that estimates the (long-term, steady-state) fraction of time a WS is available to complete its assigned missions. A new concept for readiness called endurance supply (Es) has recently been developed. Es aims at providing an alternative readiness metric by measuring how long the onboard inventory can keep a system operating. This begs the question of what relationships exist between both metrics, and, whether or not, under certain conditions, Es should be used for planning purposes in lieu of (or, in addition to) Ao. This research provides insight into those questions by conducting experimental analysis on a series of naval aviation WS. The research motivation is the suspicion that high Ao may not translate to short-term readiness in contested environments. That is, there is no guarantee that allowance packages generated to meet Ao standards will be useful if a ship must operate in a no-resupply environment. Es aims to complement Ao for use in spare parts allowancing by measuring the number of days a given allowance list can sustain WS at a site without resupply. This research supports one of the four CNO’s Navigation Plan top objectives: Readiness; that is, the ability to deliver a fleet prepared to meet its mission. Due to their sensitivity, distribution of findings, conclusions, and recommendations is restricted. For further information, refer to the technical report.Approved for public release. Distribution is unlimited.This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)N4 - Material Readiness & Logistic
MARFORRES Realignment Operation FY15 MID-YEAR REPORT
No full textNaval Research ProgramPrepared for: Commander, Marine Forces ReservePoint of Contact: Mr. Robert McGuines
A Methodology for Evaluating Decisions in the Navy's POM Process
No full textNPS NRP Executive SummaryBased on air-cargo demand data provided by The Navy Air Logistics Office (NALO), we have analyzed the Fleet Logistics Support Wing’s (FLSW) current operational practices and squadron allocation, with the objective of identifying potential improvements in operations and deployment (i.e., re-allocation). We have addressed two main questions: 1. Given the current deployment of aircraft in bases, can we improve the employment of aircraft, that is, the assignment of aircraft from bases to missions? 2. Can we improve the deployment of aircraft, that is, the allocation of aircraft to bases? We have developed two variants of a mixed-integer program (MIP) that address these two questions. One variant is called employment model, and the other is called deployment model. The employment model, which optimizes assignments of aircraft to missions, is run twice: once with respect to the current FLSW deployment of aircraft, and once with respect to a redeployment of aircraft in bases, which results from running the deployment optimization model. With these models, we identify some inefficiencies in the current operations and propose directions for improvement. For example, we recommend redeploying aircraft such that more aircraft are allocated to bases closer to the higher U.S. Navy fleet concentration areas. Specifically, move aircraft from Naval Air Facility Washington and Andrews Air Force Base, and Naval Air Station (NAS) Fort Worth, to NAS Oceana in Virginia Beach, NAS North Island in San Diego, and NAS Point Mugu in CA. In our optimization-simulation runs, such reallocations could yield cost savings averaging about 3%, under the constrained allocation.Approved for public release. Distribution is unlimited.This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)N9 - Warfare System
Aviation Depot Maintenance Throughput Optimization
No full textNPS NRP Executive SummaryAviation Depot Maintenance Throughput OptimizationApproved for public release. Distribution is unlimited. This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)N8 - Integration of Capabilities & Resource
VLS Missile Mix, Firing Policy, and Deterrence Against Red Salvos
No full textNPS NRP Executive SummaryOverview: Vertical launch system (VLS) is the current method to fire missiles from surface naval vessels and nuclear submarines. With the transition to distributed maritime operations (DMO), the USN would like to increase the offensive capability of VLS. The appropriate mix of missiles in VLS is tied to the firing policy to counter an incoming threat. A common firing policy is shoot-shoot-look-shoot-shoot (SSLSS). The "look" is battle damage assessment (BDA) to determine the outcome of the first two shots. With enhanced technology, SSLSS might be overly conservative in using scarce resources for defensive measures. In this project we will focus on determining the optimal mix of missiles in a VLS and the corresponding firing policy. Research Questions: What VLS loadouts strike a proper balance between offensive and defensive postures? What defensive firing policy (e.g., Shoot-Shoot-Look-Shoot-Shoot, Shoot-Look-Shoot) is more effective in a given scenario? How important is BDA time in the solution? (i.e., under what BDA time-windows would a given solution remain optimal?) How can soft-kill weapons (chaff, flare, electronic counter-measures) enhance Blue's effectiveness? Research Plan: We will initially focus on simple models. For example: Red fires n homogenous missiles in its salvo and Blue has m homogenous defensive missiles to counter. We will consider variants with and without BDA. Later we will develop optimization models to examine the optimal VLS missile mix and corresponding firing policy. These will be based on the weapon target assignment problem, but incorporate constraints specific for the VLS context. Initially we will focus on what missiles should go on the VLS and how should Blue employ them. Deliverables: Final report, IPRs, poster, exec summary, algorithmsApproved for public release. Distribution is unlimited. This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)N8 - Integration of Capabilities & Resource
Theater Torpedo Inventory Optimization
No full textNPS NRP Project PosterAnti-submarine warfare (ASW) is a core mission area for the U.S. Navy and an essential component in achieving sea control. The allocation of torpedoes in support of ASW across a U.S. Fleet is currently a manual process based on shore-based personnel's experience or historical norms. This study will analyze the impact of torpedo loadouts incorporating a complex set of constraints ranging from platform capabilities to probability of kill. A mixed-integer program will be used to compare the effectiveness of different torpedo loadouts. The goal of this work is to maximize the probability of a successful outcome in a theoretical campaign against anticipated submarine threats.Approved for public release. Distribution is unlimited. This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)N8 - Integration of Capabilities & Resource
Optimally Locating MARFORRES Units
No full textJavier Salmeron and Rob DellThe U.S. Marine Forces Reserve (USMCR, MARFORRES) is conducting realignment studies where discretionary changes may benefit from formal mathematical analysis. This study has developed an optimization tool to guide and/or support Commander, MARFORRES (CMFR) decisions. A prototype of the optimization tool has been tested with data from the units and Reserve Training Centers (RTCs) in the San Francisco, CA and Sacramento, CA areas.Naval Research ProgramPrepared for: MARFORRES, POC: Mr. Gerald Ormero
Theater Torpedo Inventory Optimization
No full textNPS NRP Technical ReportAnti-submarine warfare (ASW) is a core mission area for the U.S. Navy and an essential component in achieving sea control. The allocation of torpedoes in support of ASW across a U.S. Fleet is currently a manual process based on shore-based personnel's experience or historical norms. This study will analyze the impact of torpedo loadouts incorporating a complex set of constraints ranging from platform capabilities to probability of kill. A mixed-integer program will be used to compare the effectiveness of different torpedo loadouts. The goal of this work is to maximize the probability of a successful outcome in a theoretical campaign against anticipated submarine threats.Approved for public release. Distribution is unlimited. This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)N8 - Integration of Capabilities & Resource
Theater Torpedo Inventory Optimization
No full textNPS NRP Executive SummaryAnti-submarine warfare (ASW) is a core mission area for the U.S. Navy and an essential component in achieving sea control. The allocation of torpedoes in support of ASW across a U.S. Fleet is currently a manual process based on shore-based personnel's experience or historical norms. This study will analyze the impact of torpedo loadouts incorporating a complex set of constraints ranging from platform capabilities to probability of kill. A mixed-integer program will be used to compare the effectiveness of different torpedo loadouts. The goal of this work is to maximize the probability of a successful outcome in a theoretical campaign against anticipated submarine threats.Approved for public release. Distribution is unlimited. This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)N8 - Integration of Capabilities & Resource
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