To reduce domestic military infrastructure, the United States enacted two laws that instituted rounds of base realignment and closure (BRAC) in 1988, 1991, 1993, and 1995. As a result of these BRAC rounds, the United States Army has closed or realigned 139 installations. Environmental cleanup is almost $2.3 billion (43%) of the entire cost associated with the closure and realignment of these 139 Army installations. The United States Army Base Realignment and Closure Office (BRACO) uses an...
Topic: Stochastic Optimization
Taiwan is prone to many natural disasters, especially typhoons. This thesis adapts an existing stochastic prepositioning optimization model to create a tool for Taiwan military disaster recovery planners, and then uses experimental design techniques to systematically explore solutions. The goals are to minimize the expected number of casualties and unmet commodities demands, and to determine the average number of workers deployed in response to each scenario. A design of experiments methodology...
Topics: design of experiments, stochastic optimization, foreign disaster relief
Mendeley Climate Change Library
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Jul 6, 2019
07/19
by
Mohammad Ramshani; Anahita Khojandi; Xueping Li; Olufemi Omitaomu
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Photovoltaic (PV) panels directly convert sunlight into electricity; but, sunlight also heats the panels, negatively impacting their efficiency. Green roofs are vegetative layers grown on rooftops, mainly to provide added insulation on the roof to save energy. Green roofs also cool near-surface air temperature. Hence, the joint installation of PV panels and green roofs may potentially lead to higher efficiency of PV panels in certain climates. We develop a two-stage stochastic programming model...
Topics: Climate change, Energy savings, Renewable energy generation, Stochastic optimization
As outlined in the Paris Agreement on climate change, efforts to mitigate and adapt to climate change will require new modes of development of the energy sector including the transformation and expansion of power systems to low-carbon and more resilient designs. However, there is a need for more systematic tools to support decision-making processes in the context of climate change impacts and adaptation strategies for the energy and power sectors. For instance, quantitative approaches should be...
Topics: Adaptation strategies, Climate change, Hydro-dominated, Power system, Stochastic optimization
Due to the depletion of traditional resources and the deterioration of environmental quality, Dalian has always encouraged the explorations and utilizations of renewable energy sources. The research objective of this study is to develop a multi-objective stochastic chance constrained programming (MOSCCP) model for assisting local government to design and execute rational energy exploration and management strategies. The main advantage of this model is that it effectively broadens the decision...
Topics: Climate change, Dalian, Multi-objective programming, Renewable energy structure, Stochastic...
The U.S. Navy’s supply chain stretches globally, supporting the fleet in multiple theaters to enable sustained forward presence, security, and deterrence. However, supply chains are subject to disruptions that slow materiel movements throughout the network, and these disruptions may severely hinder the readiness of ships operating in distant theaters. A common culprit for peacetime supply chain disruptions is adverse weather, which is especially true in waters that are prone to major tropical...
Topics: optimization, supply chain disruption, stochastic optimization, linear programming, chance...
Counterdrug operations are of national interest to the U.S. and our allies because the illegal production and trafficking of drugs threatens U.S. national security and undermines security and stability in Latin America. Since law enforcement tasked with counterdrug operations is not given enough platforms to search every location at all times, they must decide how to employ their scarce platforms. To assist law enforcement, we develop a defender-attacker optimization model that utilizes...
Topics: Stochastic Optimization, Dynamic Programming, Defender-Attacker Optimization, Global Bender’s...
According to Department of Defense (DOD) Instruction 2205.02 (June 23, 2014), DOD components must conduct humanitarian and civic assistance (HCA) activities in response to regional conflicts or natural disasters. The Under Secretary of Defense for Policy determines how HCA policy is coordinated and implemented within the DOD and delegates responsibility to the regional combatant commands. In past modeling efforts for disaster relief, stochastic optimization has been utilized and produced...
Topics: Naval logistics, foreign humanitarian assistance, FHA, design of experiments, DOE, stochastic...
In an effort to impede the flow of drugs from South America, a Coalition Force headed by Joint Interagency Task Force (JIATF) - South allocates its assets to detect and interdict drug smuggling vessels such as the self-propelled semi-submersible (SPSS) used by a Drug Trafficking Organization (DTO). In this thesis, we develop an interdiction model to place the Coalition Force assets optimally. We also develop a model - known as the Adaptive Evader Model - for a DTO that is able to learn the...
Topics: Stochastic model, Dynamic programming, Stochastic optimization, Multiarmed bandit problem, Cross...
This thesis describes a stochastic, network interdiction optimization model to guide defensive, counter-air (DCA) operations planning. We model a layered, integrated air-defense system, which consists of fighter and missile engagement zones. We extend an existing two-stage, stochastic, generalized-network interdiction model by Pan, Charlton and Morton, and adapt it to DCA operations planning. The extension allows us to handle multiple-type interdiction assets, and constrain the attacker's...
Topics: Air defenses., Stochastic Optimization, Defender-Attacker Sequential Model, Mixed Integer...
Across defense, homeland security, and law enforcement communities, leaders face the tension between making quick but also well informed decisions regarding time-dependent entities of interest. For example, consider a law enforcement organization (searcher) with a sizable list of potential terrorists (targets) but far fewer observational assets (sensors). The searcher's goal being to follow the target, but resource constraints make continuous coverage impossible, resulting in intermittent...
Topics: applied probability, stochastic optimization, machine learning, discrete time Markov chains,...
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May 31, 2020
05/20
by
Ricardo A. Collado
data
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Data used in experiments for resource allocation for contingency planning. The experiments are discussed in details in R.Collado, S.Moazeni, " Resource Allocation for Contingency Planning: An Inexact Proximal Bundle Method for Stochastic Optimization" , in preparation. A 7z unzipper is required to open the data folder. The data folder contains the following files: Net_*.pkl : Network files containing a network graph description. Par_N*_SC*_Ver*.pkl : Files containing scenarios and...
Topics: contingency planning, risk, stochastic optimization
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Topics: Flexible backhaul, heterogeneous networks, cross-layer radio resource management, two timescale...
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368
Mar 13, 2012
03/12
by
Martin Pelikan, Mark W. Hauschild and Fernando G. Lobo
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Estimation of distribution algorithms (EDAs) guide the search for the optimum by building and sampling explicit probabilistic models of promising candidate solutions. However, EDAs are not only optimization techniques; besides the optimum or its approximation, EDAs provide practitioners with a series of probabilistic models that reveal a lot of information about the problem being solved. This information can in turn be used to design problem-specific neighborhood operators for local search, to...
Topics: estimation of distribution algorithms, evolutionary computation, stochastic optimization,...
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Mar 22, 2021
03/21
by
Seong-Cheol Kim, Papia Ray, Surender Reddy Salkuti
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This paper proposes quick & accurate islanding detection technique for a distribution system with distributed generators (DGs). Here two schemes of islanding detection based on signal processing is proposed of which one is based on discrete wavelet transform (DWT) with artificial neural network (ANN), and another one is based on S-transform with ANN. The negative sequence current/voltage signals are retrieved at targeted DG location which are used for islanding detection in the distribution...
Topics: Artificial neural networks, Distributed generation, Feature selection, Islanding detection, Signal...
