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MOR Journal Abstracts
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| Number 4 |
Risk
Management for Future Military Forces: Mapping Asymmetric Hazards (Steven
Moniz)
In the
early 1990’s the Army set the goal of incorporating risk management into all
Army programs and processes. The first step in the formal risk management process is to
create a list of hazards. The
second step is to assess the risk associated with each hazard. The ideal outcome is a perfectly prioritized list of the most
dangerous hazards. As this is not
often possible, we offer the “fuzzy risk map.”
Decision‑makers can use the risk map as a forum for discussing the
relative dangers. This will assist
in prioritizing the rest of the risk management process (decisions and actions).
The
hazard list generated for this paper is short and incomplete.
Its primary purpose is to demonstrate the use of the risk map.
The paper recommends a more formal hazard generation process, based on
challenging the assumptions of how we think we will conduct military operations
in the future. Other risk reduction
suggestions include an emphasis on redundancy, the use of conservative
estimates, and a wider base of scenarios. (Pg. 7)
Risk-Based
Methodology for Support of Operations Other Than War (Matthew Dombroski,
Yacov Y. Haimes, James H. Lambert, Kent Schlussel and Mark Sulcoski)
Since
the conclusion of the Cold War, the United States military has increasingly
participated in small-scale contingencies and operations other than war (OOTW).
An OOTW has information
requirements, rules of engagement, and interoperability considerations that are
different from conventional military operations. Lessons learned from Somalia,
Bosnia, and Kosovo highlight the need for new decisionmaking methodologies that
directly address the special needs and concerns associated with an OOTW. The
methodologies combine several forms of probabilistic risk analysis and systems
analysis to assist in decisionmaking in a joint warfare environment,
particularly at the operational level. (Pg. 19)
The
Interaction of Skill and Technology in Combat (Michael P. Fischerkeller,
Wade P. Hinkle and Stephen D. Biddle)
Is
advanced technology so important that we should accept training scale-backs, if
necessary, to afford it? Are we better served by older equipment and highly-trained
troops or cutting-edge equipment but reduced skills and readiness for at least
some parts of the force? These
questions become increasingly important as defense budgets fall, concerns
regarding readiness grow, and more and more people come to believe we face an
era of unusual technological change. Unfortunately, current technology-centric
analytical tools for informing decision-makers do not address well these
questions. A model is required that
represents how skill and technology interact to determine combat outcomes.
This article summarizes our contribution to that model-development
process. We propose a
functional form that captures the interaction of skill and technology, test its
validity using three complimentary research methods, and suggest policy and
programming implications that follow from our preliminary findings.
This paper was awarded the MORS 2000 Rist Prize. (Pg. 39)
Scaling Analysis Of Wireless Local Area Network Technology To Large Scale Battlefields (John S. Osmundson, Lance T. Arp, Mike A. Parker, Kevin J. Stewart and William G. Kemple)
The
recent Extended Littoral Battlespace (ELB) Advanced Concept Technology
Demonstration (ACTD) showed the feasibility of using wireless local area network
(WaveLAN) technology for battlefield C4ISR.
This paper reports the findings of a simulation, developed for the USMC,
that modeled an extension to the ELB WaveLAN communications architecture to
determine whether the technology could be applied to a Marine Expeditionary
Brigade (MEB), covering a 200 x 200 mile tactical battlespace.
Results show that MEB operational requirements can be met by existing
WaveLAN technology, using either conventional communications relays or an all
WaveLAN architecture. (Pg. 57)
A
Network Disruption Modeling Tool (James A. Leinart, Richard F. Deckro, Jack M. Kloeber
Jr. and Jack A. Jackson)
Identifying
network components, which when targeted will effectively disrupt a command,
control, communication, and computer (C4) network, can be a difficult task.
Since C4 networks can be very large, with components having many
characteristics, it is important to have a sound method for evaluating and
selecting targets to accomplish network disruption.
In this effort James Leinart, Dick Deckro, Jack Kloeber and Jack Jackson present a methodology for suggesting targets to disrupt a C4 network. The method uses graph theory, value-focused thinking and decision analysis techniques. A vertex cut-set algorithm is applied on a transformation of the graph representing a notional C4 network. The mixed cut-sets generated represent potential target sets, which in turn are ranked according to decision maker preferences and the overall objectives for achieving a network disruption. A decision maker or planner can use the ranked list of potential target sets to nominate targets or can pare down the list and conduct more in-depth analysis. (Pg. 69)
How Game Theory Fails To Explain Man (Fredrik A Dahl and
Bjørn Tallak Bakken)
We analyze human decision making experimentally in a simple
air campaign model (Campaign), in
order to test game theory’s explanatory power. Game theory predicts that
Campaign-playing subjects should play randomly according to a given probability
distribution. Our experiments indicate that this theory fails to explain both
how humans think, and how they act. With experience, their actions even tend to
move away from the theory’s predictions. However, our subjects consistently
improve their ability to avoid dominated actions, so it is the failure to
randomize that separates human practice from game theory, rather than failure to
identify reasonable candidate actions. (Pg. 5)
Lanchester’s Equations And The Structure of the
Operational Campaign: Between-Campaign Effects (L.R. Speight)
The main thrust of this paper is to reconcile common combat
modelling practice with the evidence stemming from the analysis of historical
battle outcomes. In many aggregated models variants of Lanchester’s ‘Square
Law’, or a ‘Square-Linear Law’, are used to represent the direct fire
attrition process. These place a heavy premium on the concentration of force
with, other things being equal, the balance of attrition strongly favouring the
side with the greater number of combatants. However, almost without exception,
the relationships actually observed in collected samples of historical battles
are in line with a ‘Log-Linear’ version of Lanchester’s equations. This
would suggest that, in attrition terms, concentration of force should positively
be avoided. The greater the number of combatants assembled on the battlefield,
the greater will be the likely number of casualties accruing to that side.
In this paper it is pointed out that the battles which
feature in historical samples are self-selecting. By definition, these samples
do not feature those instances where a would-be assailant chose not to launch an
attack because he calculated that his chances of success were negligible. Nor do
they include those occasions where the defender chose to abandon his position
because he saw that defeat was almost inevitable. For those cases that remain a
key task for the attacking commander would have been to assemble the resources
he deemed necessary to ensure a reasonable chance of mission success. In
practical terms this means that he would be prepared to enter battle with a
smaller force ratio if he perceived the opposing forces to be militarily
ineffective; if he had confidence in the prowess of his own troops; if he felt
that he had the edge in terms of weapon effectiveness; and/or if he judged that
the chances of local concentration and other terrain features were in his favour.
These sorts of considerations are in line with the between-campaign
relationships actually observed in the main historical data base assembled by UK
analysts.
This paper describes a process of theoretical modelling and
simulation, based on evidence from live trials and from battle. The results
suggest that, even though the affrays within a campaign may obey a version of
Lanchester’s ‘Square-Linear Law’, the mechanisms outlined above will
ensure that their outcomes will appear to obey a ‘Log-Linear’ relationship
when they are aggregated over a collected sample of campaigns. This effect will
be enhanced if casualties from the direct fire battle are simply combined with
those from other quasi-independent sources, such as those due to air power or
the taking of prisoners. (Pg. 15)
Performance Analysis in the Selection of Imagery
Intelligence Satellites (Roger C. Burk, Carolina Deschapelles, Karl Doty,
Jonathan E. Gayek and Thomas Gurlitz)
In 1999, the National Reconnaissance Office was ready to buy
a complete replacement for its system of photoreconnaissance satellites.
A number of different proposals had been submitted by different
companies. The authors helped plan
and execute the performance analysis component of this multi-billion-dollar
source selection decision. Our framework was a multiattribute value decomposition.
The metrics were evaluated using a wide variety of techniques, including
linear, non-linear, and integer optimization, continuous and discrete-event
simulation, network flow analysis, and a genetic algorithm.
This analysis incorporated the diverse needs of intelligence users to
ensure an affordable system meeting the critical needs. (Pg. 45)
Risk Management And The Value Of Information In A Defense
Computer System (J. Todd Hamill,
Richard F. Deckro, Jack M. Kloeber Jr. and T. S. Kelso)
As our reliance upon Information Systems for a multitude of vital operations increases, so do the concomitant vulnerabilities and risks associated with their operation and implementation. This problem, further complicated by the rapid growth and complexity in information technologies, requires efficient risk management within technical and/or fiscal constraints. This article presents potential improvements upon current risk management processes by incorporating value focused thinking into the process. In this approach, based on a test case with a DoD local area network, the value of the information served as a focal point for prioritizing vulnerabilities requiring remedy, thereby facilitating the efficient reduction of risk inherent in today’s information systems. (Pg. 61)
A
Structural Equation Modeling Analysis of Naval Readiness (B. Charles Tatum)
The
past downsizing of the Department of Defense, the expansion into new operational
settings (e.g., peace keeping, drug interdiction), and the terrorist attacks on
9/11/01 have caused some officials to wonder whether the military is adequately
prepared for today’s threats. Several reports by the Congressional Budget
Office and the Defense Science Board have concluded that the readiness of the
Armed Forces is still adequate relative to historical levels. This conclusion,
however, may be based on a seriously flawed set of measures.
This study investigates the feasibility of modeling the readiness process
using Structural Equation Modeling (SEM). The
results indicate that SEM can reasonably represent the human components of the
readiness process, and that future studies on military readiness should adopt
this statistical technique. The paper was named the best presentation in Working
Group 21 of the Military Operations Research Society Symposium, June 1999. (Pg.
5)
A
Fractal-Based Approach To Equations Of Attrition (Michael K Lauren)
Recent land and joint operations highlight a trend towards greater dispersion of forces on the battlefield. This is particularly true when an operation is not traditional warfare (for example, part of a peace enforcement mission). Current methods struggle to describe the dispersed battlefield, particularly when the participants do not necessarily follow one particular doctrine. This paper uses a cellular-automaton tool to explore dispersed battlefields. It is shown how the results of this modeling differ from more traditional approaches such as the Lanchester equation. These results have contributed to force structure studies currently in progress for the New Zealand Army, in particular, pointing to the value of human intelligence and C2 networks. (Pg. 17)
Balancing Promise and Risk with Information Assurance in Joint Vision 2020 (Yacov Y. Haimes, Thomas A. Longstaff and Gregory A. Lamm)
Joint Vision 2020 (JV2020) builds upon and extends the conceptual template established by Joint Vision 2010 to guide the continuing transformation of America’s Armed Forces. Its major premise is the ability to achieve military superiority by maintaining dominance in information technology. Identifying and understanding the myriad risks associated with the military’s quest for information superiority constitute an imperative for their ultimate management. To do so, the authors present a systemic methodology for identifying the sources of risk, and a methodology for filtering and reducing them to a manageable number. The authors also address the needs for appropriate education, training, and knowledge management to meet the goals of JV2020. (Pg. 31)
Joint Services Conference on the Uses of History for Analysis and Military Planning (JCHAMP)
No Abstract (Pg. 47)Probabilistic Modeling of Terrorist Threats: A Systems Analysis Approach to Setting Priorities Among Countermeasures (Elisabeth Paté-Cornell and Seth Guikema)
Setting priorities among
homeland defense measures is a difficult task given the large number of possible
scenarios and the uncertainties about the probabilities and impacts of the
possible types of attacks. This paper presents a model for setting priorities
among threats and among countermeasures, based on probabilistic risk analysis,
decision analysis, and elements of game theory. This model accounts for the
probabilities of different scenarios, the objectives of both the terrorists and
the U.S., and the dynamic competition between them. The model presented is
useful for ranking countermeasures at a number of levels in the U.S. government.
(Pg. 5)
Applying Bayesian Belief Networks as a Tool
For Structuring and Evaluating The Planning of Naval Operations (Martin
Kidd)
Bayesian belief networks and influence diagrams are excellent methodologies for structuring complex planning problems under conditions of uncertainty and were applied to the process of operational planning of naval campaigns. This article describes how influence diagrams were used in the operations planning process of the South African Navy and the successes achieved. Influence diagrams enable the planning team to determine decisions and factors influencing the pending campaign in a structured manner. Conditional probability tables quantify the interrelationships between factors and decisions, and in the process a probabilistic model of the campaign is built. It allows the team to concentrate on small subsets of the campaign without losing sight of the whole. The network also serves as a tool for answering what-if questions. (Pg. 25)
Modeling Information Assurance: An Application
(Joseph E.
Beauregard, Richard F. Deckro
and
Stephen P. Chambal)
The
ever-increasing speed of information systems allows
decision-makers around the world to gather,
process, and disseminate information almost instantaneously.
However, this benefit comes with a price. Information is valuable and
therefore a target to those who do not have it or wish to destroy
it. The Department of Defense (DoD)
often cannot sacrifice the speed at which this
information is currently processed and disseminated and it
must find ways to assure its protection. There
has been some effort to model information
assurance in recent years, however no simple, accepted, quantifiable
model currently exists. This study establishes
an Information Assurance Analysis Model (IAAM)
to aid organizations, specifically organizations
within the Department of Defense (DoD), in their efforts to protect
valuable information and information systems. The model is first
developed and then applied to an actual classified system. While organizations
will have to fine-tune the model to their specific needs, the article presented
here does provide an application of the general framework. (Pg.35)
An Analysis of the Efficiency of Joint Advertising Versus Service-Specific Advertising for Military Recruitment (Patrick L. Brockett, William W. Cooper, Honghui Deng, Linda Golden, Michael J. Kwinn, Jr. and David A. Thomas)
A study conducted for DOD by the Wharton Center for Applied Research assembled a large body of data to examine the relative advantages of Joint (all services) vs. Service Specific Advertising for military recruitment. Statistical analyses by Wharton and RAND failed to take account of the efficiencies displayed by different Battalions in their recruitment performances. Joint Advertising is shown to be superior when this is not taken into account. However, when adjustments are made for efficiency this result is reversed and Service Specific Advertising is found to be superior. This is a new approach based on DEA (Data Envelopment Analysis) which will be explored further in later papers. (Pg. 57)
A Theory of Judgement Aggregation in a
Hierarchical Setting Using Markowitz Portfolio Theory (W.J. Hurley and
W.J. Graham)
In the case where a commander and his staff have to assess an uncertain quantity, this paper uses Markowitz portfolio theory to develop some principles which ought to guide the commander’s assessment of staff opinion. Among others these include the conditions under which a commander ought to entertain the opinion of an idiot, and conditions for which the opinion of a “yes-man” are useful. (Pg.77)
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