OR, Defence and Security

Although a considerable prehistory of some of its ideas and motivations can be identified in a wide range of earlier endeavours, the name ‘operational research’ (OR) and its recognition as a distinct scientific discipline have their origins in the defence domain.

The Operational Analysis (OA) Branch of the HQ ARRC deployed into Kosovo concurrently with the withdrawal of Serbian forces. The authors, all members of the Operational Analysis Branch, were responsible for providing general scientific, and more specifically Operational Research, advice to General Jackson, Commander of the Kosovo Force. This paper outlines the work done by OA Branch leading up to, and during the challenging period from the first deployment of troops into Kosovo in June 1999 to October 1999. The work of the branch was in two major sections; the first, support to returning Kosovo to normality and the second, to monitor the compliance of the Kosovo Liberation Army (UCK) with the undertaking to demilitarise. OA Branch provided not only the military with work to quantify the return to normality, but also worked with and provided data to aid agencies. The work ranged from assessments of damage to the infrastructure of Kosovo, particularly the housing, through to the monitoring of crime. The population estimates produced by the branch corrected the emotive image being produced in the media, and became the subject of an international press conference. OA Branch’s weekly Compliance Monitoring report was the authoritative document for checking on the progress of the UCK towards demilitarisation; this coupled with work on trends in violence were regularly briefed to the KFOR Commander.

There is a need to represent military command and control in closed-form simulation models of conflict, in order to compare investment in such capability with alternative defence investments. This paper considers such representation of military command and control in the context of embodied cognitive science. This means that we represent such processes in terms of both decision-making and resultant behaviour. Previous work leads to the view that such a representation can be captured by a combination of deliberate (top down) planning and rapid (bottom up) planning. We have developed an approach on these lines as a way of representing human decision-making and behaviour in conflict. Here we show, by comparing simulation model results with real conflict situations, that our approach yields emergent force behaviour which is valid and representative. This thus increases our confidence that our representation of command and control in such simulation models is sufficient for our requirements.

This paper firstly discusses the modelling of Peace Support Operations (PSO) within the defence simulation modelling context. It then provides a summary background of the current relevant approaches in such modelling, taking account of the increasing complexity of the strategic environment, and the relevance of ideas from Complex Adaptive Systems theory. It goes on to describe the details of two agent-based models spanning the problem domain, which capture the key ideas of complexity, within a PSO context, taking account of the complex interactions between peacekeepers, civilians, insurgents and nongovernmental organisations involved.

Using an agent-based model as a ‘battlefield laboratory’, we explore equations of combat attrition which extend beyond the conventional Lanchester equations and which endeavour to encapsulate the more complex aspects of warfare. Our approach compares predictions from candidate attrition equations with casualty data generated artificially from an agent-based model. For situations where the initial regimented structure of the fighting forces breaks down, introducing fractal concepts into the attrition equations proves effective at encapsulating complex aspects of the battle; with details in the time dependence of the casualty data able to be reproduced. Furthermore, measuring the fractal dimension of a fighting force’s spatial distribution on the battlefield provides a sensitive probe of the combatants’ behaviour. Precise timesat which key events occur duringa battle can be pinpointed. This study furthers the body of work which considers warfare as a complex adaptive system and where fractal-like structures are expected to emerge.

Many authors have used dynamical systems to model asymmetric war. We explore this approach more broadly, first returning to the prototypical such models: Richardson’s arms race, Lanchester’s attrition models and Deitchman’s guerrilla model. We investigate combinations of these and their generalizations, understanding how they relate to assumptions about asymmetric conflict. Our main result is that the typical long-term outcome is neither annihilation nor escalation but a stable fixed point, a stalemate. The state cannot defeat the insurgencybyforcealone,butmustalterthe underlyingparameters.Weshowhow our models relatetoor subsume other recent models. This paperisaself-contained introduction to 2D continuous dynamical models of war, and we intend that, by laying bare their assumptions, it should enable the reader to critically evaluate such models and serve as a reminder of their limitations.

This paper describes an experimental method for determining the value of different types of information to military decision makers. The experimental method used a simple scenario and a set of serials constructed from cards, each presenting a single piece of information and presented sequentially. Each of a number of pairs of players were taken through the scenario and asked to judge how they would respond to the situation. This paper extends on the method presented in previous papers to consider the case of a decision in which the response can both increase and decrease as more information is presented. This allows a more general military problem to be considered, that of risk-taking behaviour in response to the possibility of chemical, biological, radiological or nuclear events.

The Canadian Forces (CF) is seeking to establish permanent and temporary operational support hubs at strategic locations around the globe to improve its logistics support effectiveness and responsiveness for deployed operations. This paper addresses two logistics problems associated with the hub-based support concept, namely, hub location optimization and aircraft routing problems. A discrete facility location model was developed to analyse the hub-based support effectiveness and to determine the optimal hub locations. An aircraft routing model was also developed to determine optimal aircraft routes for the movement of cargo and supplies from various support hubs to a theatre of operation. Both models were formulated using mixed integer nonlinear programming. Historical CF deployment and sustainment data were used to conduct the analysis and to illustrate the methodology. The study indicates that the hub-based support approach would offer potential cost avoidance on sustainment lift and could be an effective strategy for improvement of the CF’s support capability. It also indicates that potential lift costs could be avoided through optimal routing of sustainment flights.

Benefits Analysis has been evolving over the past decade from roots in multi-criteria analysis, causal mapping and multi-methodology. It has now reached a level of maturity such that it deserves to be treated as a method in its own right, and this paper seeks to document the method and provide guidance on its use. Benefits Analysis is a systematic method for formulating complex, multi-factor investment appraisal problems where decision-makers seek to realize non-financial benefits. Such decision problems abound in military OR, particularly the management of equipment capability and research. Benefits Analysis connects qualitative and quantitative OR methods and facilitates robust assessment, including multi-methodology. This paper describes the principles of Benefits Analysis and discusses its application to a variety of real problems, including research management, capability management, balance of investment, business case development and benefit quantification strategies.

Defence forces continue to evolve as new technologies, approaches to warfare and roles are introduced. With defence being a significant ongoing investment for any nation, and with the typical longevity of the capabilities involved, there are challenges in developing a robust force able to meet its national interests against a backdrop of a changing strategic landscape and constrained budgets. In an effort to address these challenges, an analytical construct has been developed for experimentation that provides a traceable linkage from government guidance through to the capability implications. A key component of the construct is to provide those involved in experimentation exercises with a suitable representation of an active dynamic adversary who is able to stress their responses and expose key vulnerabilities and potential capability tipping points. The principle adopted is that more is learnt by examining the breaking points of the system. This paper outlines the framework and some of the tools and techniques developed in its support. The proposed construct also incorporates a level of scrutiny to establish confidence in results obtained. The framework has been successfully applied to the Australian Defence Capability Program.

Determining the pattern of links within a large social network is often problematic due to the labour-intensive nature of the data collection and analysis process. With constrained data collection capabilities it is often only possible to either make detailed observations of a limited number of individuals in the network, or to make fewer observations of a larger number of people. Previously we have shown how detailed observation of a small network can be used, which infer where in the network previously unconnected individuals are likely to fit, thereby attempting to predict network growth as new people are considered for inclusion. Here, by contrast, we show how social network topology can be inferred following a limited observation of a large network. Essentially the issue is one of inferring the presence of links that are missed during a constrained data collection campaign on the network. It is particularly difficult to infer network structures for those organizations that actively seek to remain covert and undetected. However, it is often very useful to know if two given individuals are likely to be connected even though limited surveillance effort yields no evidence of a link. Specifically, we show how a statistical inference technique can be used to successfully predict the existence of links that are missed during network sampling. The procedure is demonstrated using network data obtained from open source publications.

Terrorism with weapons of mass destruction (WMDs) is an urgent threat to homeland security. The process of counter-WMD terrorism often involves multiple government and terrorist group players, which is under-studied in the literature. In this paper, first we consider two subgames: a proliferation game between two terrorist groups or cells (where one handling the black market for profits proliferates to the other one to attack, and this is modelled as a terrorism supply chain) and a subsidization game between two governments (where one potential WMD victim government subsidizes the other host government, who can interfere with terrorist activities). Then we integrate these two subgames to study how the victim government can use the strategy of subsidization to induce the host government to disrupt the terrorism supply chain. To our knowledge, this is the first game-theoretic study for modelling and optimally disrupting a terrorism supply chain in a complex four-player scenario. We find that in the integrated game, when proliferation payment is high or low, the practical terrorist group will proliferate and not proliferate, respectively, regardless of government decisions. In contrast, in the subsidization subgame between the two governments, the decision of subsidization depends on its cost. When proliferation payment is medium, the decision of subsidization depends on not only its cost but also the preparation cost and the attacking cost. Findings from our results would assist in government policymaking.