Organization:
Center for Infrastructure Defense (CID)

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The Center for Infrastructure Defense (CID) focuses on the continued operation of critical military and civilian infrastructure in the presence of accident, failure, and attack. Our team combines the expertise of senior scholars with a highly motivated student body consisting of military officers and government employees from the U.S. and its global partners. We serve as trusted advisors to the military, government, and private sector. We stand ready to address both long-term and emergent issues related to national and international infrastructure systems.
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Publication Search Results

Now showing 1 - 10 of 24
  • Publication
    Optimizing Military Capital Planning
    (2004) Brown, Gerald G.; Dell, Robert F.; Newman, Alexandra M.; Center for Infrastructure Defense (CID); Department of Operations Research
    Planning United States military procurement commits a significant portion of our nation’s wealth and deter- mines our ability to defend ourselves, our allies, and our principles over the long term. Our military pioneered and has long used mathematical optimization to unravel the distinguishing complexities of military capital planning. The succession of mathematical optimization models we present exhibits increasingly detailed fea- tures; such embellishments are always needed for real-world, long-term procurement decision models. Two case studies illustrate practical modeling tricks that are useful in helping decision makers decide how to spend about a trillion dollars.
  • Publication
    The "Robust Yet Fragile" Nature of the Internet
    (2005) Alderson, D.; Roughan, M.; Shalunov, S.; Tanaka, R.; Willinger, W.; Doyle, J.; Li, L.; Low, S.; Center for Infrastructure Defense (CID); Department of Operations Research
    The search for unifying properties of complex networks is popular, challenging, and important. For modeling approaches that focus on robustness and fragility as unifying concepts, the Internet is an especially attractive case study, mainly because its applications are ubiquitous and pervasive, and widely available expositions exist at every level of detail. Nevertheless, alternative approaches to modeling the Internet often make extremely different assumptions and derive opposite conclusions about fundamental properties of one and the same system. Fortunately, a detailed understanding of Internet technology combined with a unique ability to measure the network means that these differences can be understood thoroughly and resolved unambiguously. This article aims to make recent results of this process accessible beyond Internet specialists to the broader scientific community and to clarify several sources of basic methodological differences that are relevant beyond either the Internet or the two specific approaches focused on here (i.e., scale-free networks and highly optimized tolerance networks).
  • Publication
    A Stochastic Program for Optimizing Military Sealift Subject to Attack
    (2009) Morton, D.P.; Salmerón, J.; Wood, R.K.; Center for Infrastructure Defense (CID); Department of Operations Research
    We describe a stochastic program for planning the wartime, sealift deployment of military cargo that is subject to attack. The cargo moves on ships from U.S. or allied seaports of embarkation, to seaports of debarkation (SPODs) near the theater of war where it is unloaded and sent on to final, in-theater destinations. The question we ask is: Can a deployment-planning model, with proba- bilistic information on the time and location of potential enemy attacks on SPODs, suc- cessfully hedge against those attacks? That is, can this information be used to reduce the expected disruption caused by such attacks? We develop a specialized, stochastic mixed-integer program whose solutions answer that question in the affirmative for realistic deployment data. Furthermore, compared to the optimal deterministic so- lution, the stochastic solution incurs only a minor"disruption penalty" when no attack occurs, and outcomes for worst-case sce narios are better. Insight gained from the stochastic-programming approach also points to possible improvements in current, rule- based, scheduling methods.
  • Publication
    Anatomy of a Project to Produce a First Nuclear Weapon
    (2006) Brown, G.; Carlyle, M.; Harney, R.; Skroch, E.; Wood, K.; Center for Infrastructure Defense (CID); Operations Research (OR)
    We describe the industrial project that a “proliferator” would conduct to produce a first, small batch of nuclear weapons. From refining yellowcake ore to final weapons assem- bly, we highlight the project’s tasks and their interactions. The proliferator can choose alternative production technologies that offer quicker completion, but at higher cost in terms of limited resources. The proliferator can also expedite his project by devot- ing more resources to critical tasks. From physics and chemistry, we determine raw material requirements. From industrial engineering and materials science, we convert these requirements into estimates of the time, manpower, energy, and money required to complete each task under normal and expedited conditions. Using generalized project- management analysis tools, we then estimate the earliest possible completion time of the project, assuming two different levels of resource availability. We also estimate the time required to complete a weapon if some of the project’s steps can be skipped; for example, if the proliferator acquires stolen, highly enriched uranium metal.
  • Publication
    Stochastic Network Interdiction
    (1998) Cormican, K.J.; Morton, D.P.; Wood, R.K.; Center for Infrastructure Defense (CID); Department of Operations Research
    Using limited assets, an interdictor attempts to destroy parts of a capacitated network through which an adversary will subsequently maximize flow. We formulate and solve a stochastic version of the interdictor’s problem: Minimize the expected maximum flow through the network when interdiction successes are binary random variables. Extensions are made to handle uncertain arc capacities and other realistic variations. These two-stage stochastic integer programs have applications to interdicting illegal drugs and to reducing the effectiveness of a military force moving materiel, troops, information, etc., through a network in wartime. Two equivalent model formulations allow Jensen’s inequality to be used to compute both lower and upper bounds on the objective, and these bounds are improved within a sequential approximation algorithm. Successful computational results are reported on networks with over 100 nodes, 80 interdictable arcs, and 180 total arcs.
  • Publication
    Optimizing Army Base Realignment and Closure
    (1998) Dell, Robert F.; Center for Infrastructure Defense (CID); Department of Operations Research
    In April 1997, the United States Army announced that savings had finally overtaken costs in closing or realigning 803 of its installations worldwide. This milestone occurred in the ninth year of a 13-year program approved by Congress and Presi- dents Reagan, Bush, and Clinton. The cost of this program is $5.3 billion, and when complete, the army expects annual sav- ings of $996 million in perpetuity. A mixed-integer linear pro- gram, BRACAS (base realignment and closure action schedu- ler), helped the army budget for the 29 closures and 11 realignments approved by Congress and President Clinton in 1995. The army used BRACAS to schedule optimally the $2 billion in BRAC costs for these 40 installations over the six- year period mandated by Congress; associated annual savings will be $360 million.
  • Publication
    Shortest‐Path Network Interdiction
    (2002) Israeli, E.; Wood, R.K.; Center for Infrastructure Defense (CID); Department of Operations Research
    We study the problem of interdicting the arcs in a net- work in order to maximize the shortest s–t path length. “Interdiction” is an attack on an arc that destroys the arc or increases its effective length; there is a limited inter- diction budget. We formulate this bilevel, max–min prob- lem as a mixed-integer program (MIP), which can be solved directly, but we develop more efficient decompo- sition algorithms. One algorithm enhances Benders de- composition by adding generalized integer cutting planes, called “supervalid inequalities” (SVIs), to the master problem. A second algorithm exploits a unique set-covering master problem. Computational results demonstrate orders-of-magnitude improvements of the decomposition algorithms over direct solution of the MIP and show that SVIs also help solve the original MIP faster.
  • Publication
    Optimization of Purchase, Storage and Transmission Contracts for Natural Gas Utilities
    (1992) Avery, W.; Brown, G.G.; Rosenkranz, J.; Wood, R.K.; Center for Infrastructure Defense (CID); Department of Operations Research
  • Publication
    Making Terrorism Risk Analysis Less Harmful and More Useful: Another Try (Response)
    (2011) Brown, G.; Cox, L.; Center for Infrastructure Defense (CID); Department of Operations Research
    Although Ezell claims that we only “repackaged in a new article the limitations identified by Ezell et al. of PRA in terrorism risk analysis,” he neither ad- dresses nor refutes any of our substantive technical points and examples, and his comments reflect a fundamental lack of understanding of our main ideas. We are therefore grateful for this opportunity to clarify our reasoning in light of his comments, as follows.
  • Publication
    Real-Time, Wide Area Dispatch of MOBIL Tank Trucks
    (1987) Brown, G.G.; Ellis, C.; Ronen, D.; Center for Infrastructure Defense (CID); Department of Operations Research
    Mobil Oil Corporation has adopted a completely integrated, highly automated, real-time computer system for centralized control of distribution to customers in the continental United States of light petroleum products: gasolines, diesel, heating oil, and so forth. This system manages all aspects of marketing and distribution, from order entry via an audio response computer through credit checking, delivery, and billing operations that annua!ly generate $4 billion in sales on 600,000 customer orders and that use 120 bulk terminals and a fleet of more than 430 vehicles. The heart of this system is computer assisted dispatch (CAD), a collection of integer programming methods used within a real-time, transaction-driven information management system, which allots about one second, on average, per dispatch for optimization. CAD exploits the experience and knowledge of the human dispatchers it assists. Using CAD, Mobil has substantially reduced costs and staff while improving customer service.