Search

In this paper we simultaneously consider three extensions to the standard Orienteering Problem (OP) to model characteristics that are of practical relevance in planning reconnaissance missions of Unmanned Aerial Vehicles (UAVs). First, travel and recording times are uncertain. Secondly, the information about each target can only be obtained within a predefined time window. Due to the travel and recording time uncertainty, it is also uncertain whether a target can be reached before the end of its time window. Finally, we consider the appearance of new targets during the flight, so-called time-sensitive targets, which need to be visited immediately if possible. We tackle this online stochastic UAV mission planning problem with time windows and time-sensitive targets using a re-planning approach. To this end, we introduce the Maximum Coverage Stochastic Orienteering Problem with Time Windows (MCS-OPTW). It aims at constructing a tour with maximum expected profit of targets that were already known before the flight. Secondly, it directs the planned tour to predefined areas where time-sensitive targets are expected to appear. We have developed a fast heuristic that can be used to re-plan the tour, each time before leaving a target. In our computational experiments we illustrate the benefits of the MCS-OPTW planning approach with respect to balancing the two objectives: the expected profits of foreseen targets, and expected percentage of time-sensitive targets reached on time. We compare it to a deterministic planning approach and show how it deals with uncertainty in travel and recording times and the appearance of time-sensitive targets.

The Orienteering Problem (OP) is a routing problem which has many interesting applications in logistics, tourism and defense. The aim of the OP is to find a maximum profit path or tour, which is feasible with respect to a capacity constraint on the total weight of the selected arcs. In this paper we consider the Orienteering Problem with Stochastic Weights (OPSWs) to reflect uncertainty in real-life applications. We approach this problem by formulating a two-stage stochastic model with recourse for the OPSW where the capacity constraint is hard. The model takes into account the effect that stochastic weights have on the expected total profit value to be obtained, already in the modeling stage. Since the expected profit is in general non-linear, we introduce a linearization that models the total profit that can be obtained for a given tour and a given scenario of weight realizations. This linearization allows for the application of Sample Average Approximation (SAA). The SAA solution asymptotically converges to the optimal solution of the two-stage model, but is computationally expensive. Therefore, to solve large instances, we developed a heuristic that exploits the problem structure of the OPSW and explicitly takes the associated uncertainty into account. In our computational experiments, we evaluate the benefits of our approach to the OPSW, compared to both a standard deterministic approach, and a deterministic approach that is extended with utilization of real-time information. © 2013 Elsevier Ltd.

Het verwerken van e-commerce bestellingen stelt magazijnen voor grote uitdagingen. Het assortiment aan producten is vaak groot, waarmee de afstanden in het magazijn ook groot worden. Daarnaast bestaan de bestellingen meestal uit één eenheid, in plaats van uit complete dozen of pallets die kostenefficiënt te verplaatsen zijn. Daarbovenop komt dat de frequentie waarmee bestellingen binnenkomen voor een bepaald product sterk kan variëren, wat een gunstige positionering van veelgevraagde producten verhindert. Hierdoor kunnen traditionele, handmatige systemen, waarbij werkers door een magazijn lopen, erg inefficiënt zijn voor e-commerce bedrijven. Zogeheten Robotic Mobile Fulfillment Systems (RMFS) vormen een nieuwe categorie van geautomatiseerde opslag- en bestellingenverzamelingssystemen, die speciaal ontwikkeld is om e-commerce bestellingen te verwerken. Deze RMFS worden op de markt gebracht door bedrijven als Amazon Robotics (voorheen bekend als Kiva Systems), Swisslog, Interlink, Grey-Orange, Scallog en Mobile Industrial Robots. Implementaties wijzen er tot nu toe op, dat de snelheid van het verzamelen van producteenheden kan verdubbelen in vergelijking met traditionele, handmatige systemen.

This paper considers a special case of security games dealing with the protection of a large area divided in multiple cells for a given planning period. An intruder decides on which cell to attack and an agent selects a patrol route visiting multiple cells from a finite set of patrol routes such that some given operational conditions on the agent’s mobility are met. For example, the agent might be required to patrol some cells more often than others. In order to determine strategies for the agent that deal with these conditions and remain unpredictable for the intruder, this problem is modeled as a two-player zero-sum game with probabilistic constraints such that the operational conditions are met with high probability. We also introduce a variant of the basic constrained security game in which the payoff matrices change over time, to allow for the payoff that may change during the planning period.

The operational use of satellite systems has been increasing due to technological advances and the reduced costs of satellites and their launching. As such it has become more relevant to determine how to better use these new capabilities which is reflected in an increase in application studies in this area. This work focuses on the problem of developing the scheduling of a constellation of satellites and associated ground stations to monitor different types of locations (targets) with different priorities for a given planning horizon. In order to address this problem we will propose a new model that considers explicitly the operational requirements of Brazilian relevant scenarios for a given planning horizon and target priority list. The methodology to be developed to solve this model will also be discussed.

This paper considers a special case of security games dealing with the protection of a large area divided in multiple cells for a given planning period. An intruder decides on which cell to attack and an agent selects a patrol route visiting multiple cells from a finite set of patrol routes such that some given operational conditions on the agent’s mobility are met. For example, the agent might be required to patrol some cells more often than others. In order to determine strategies for the agent that deal with these conditions and remain unpredictable for the intruder, this problem is modeled as a two-player zero-sum game with probabilistic constraints such that the operational conditions are met with high probability.We also introduce a variant of the basic constrained security game in which the payoff matrices change over time, to allow for the payoff that may change during the planning period.

This paper considers a special case of security games dealing with the protection of a large area divided in multiple cells for a given planning period. An intruder decides on which cell to attack and an agent selects a patrol route visiting multiple cells from a finite set of patrol routes such that some given operational conditions on the agent’s mobility are met. For example, the agent might be required to patrol some cells more often than others. In order to determine strategies for the agent that deal with these conditions and remain unpredictable for the intruder, this problem is modeled as a two-player zero-sum game with probabilistic constraints such that the operational conditions are met with high probability. We also introduce a variant of the basic constrained security game in which the payoff matrices change over time, to allow for the payoff that may change during the planning period.

Het verwerken van e-commerce bestellingen stelt magazijnen voor grote uitdagingen. Het assortiment aan producten is vaak groot, waarmee de afstanden in het magazijn ook groot worden. Daarnaast bestaan de bestellingen meestal uit één eenheid, in plaats van uit complete dozen of pallets die kostenefficiënt te verplaatsen zijn. Daarbovenop komt dat de frequentie waarmee bestellingen binnenkomen voor een bepaald product sterk kan variëren, wat een gunstige positionering van veelgevraagde producten verhindert. Hierdoor kunnen traditionele, handmatige systemen, waarbij werkers door een magazijn lopen, erg inefficiënt zijn voor e-commerce bedrijven. Zogeheten Robotic Mobile Fulfillment Systems (RMFS) vormen een nieuwe categorie van geautomatiseerde opslag- en bestellingenverzamelingssystemen, die speciaal ontwikkeld is om e-commerce bestellingen te verwerken. Deze RMFS worden op de markt gebracht door bedrijven als Amazon Robotics (voorheen bekend als Kiva Systems), Swisslog, Interlink, Grey-Orange, Scallog en Mobile Industrial Robots. Implementaties wijzen er tot nu toe op, dat de snelheid van het verzamelen van producteenheden kan verdubbelen in vergelijking met traditionele, handmatige systemen.

Contains fulltext : 178964pub.pdf (Publisher’s version ) (Closed access) Research has shown that many individuals have difficulties solving tasks that involve a principal component of dynamic systems: accumulation. They incorrectly assume that the behavioural pattern of a stock resembles that of its flows and vice versa. This has become known as correlation heuristic reasoning. Much less is known about the underlying causes of this inability to correctly infer dynamic behaviour from graphs. We tested if two dimensions of spatial ability, spatial visualization and spatial relations, are related to selecting correct or correlation heuristic answers in tasks involving graphs over time. The analyses show that spatial visualization is positively related to performance in some systems thinking inventory tasks and is negatively related to responses that show correlation heuristic reasoning. We conclude by discussing avenues for future research into this phenomenon. 20 juni 2016 18 p.

Unmanned Aerial Vehicles (UAVs) can provide significant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specific target locations within the area of interest. In order to improve the effectiveness of a reconnaissance mission, it is important to visit the largest number of interesting target locations possible, taking into consideration operational constraints related to fuel usage between target locations, weather conditions and endurance of the UAV. We model this planning problem as the well-known orienteering problem, which is a generalization of the traveling salesman problem. Given the uncertainty in the military operational environment, robust planning solutions are required. Therefore our model takes into account uncertainty in the fuel usage between targets, for instance due to weather conditions. We report results using different uncertainty sets that specify the degree of uncertainty against which any feasible solution will be protected. We also compare the probability that a solution is feasible for the robust solution on one hand and the solution found with average fuel usage on the other. These probabilities are assessed both by simulation and by derivation of problem specific theoretical bounds on the probability of constraint feasibility. In doing so, we show how the sustainability of a UAV mission can be significantly improved. Additionally, we suggest how the robust solution can be operationalized in a realistic setting, by complementing the robust tour with agility principles

This paper presents a variant of a spare parts inventory model with cold stand-by redundancy on system level. Redundancy on system level implies that not all systems need to be operational in order to have the whole system operational. The cold stand-by feature implies that only the minimum required systems are operational. In order to determine a cost effective spare parts package such that in a cold stand-by redundancy situation a sufficient number of systems is operational for a specified period we extend the METRIC methodology. To compute the probability that the number of operating systems during the operational period is sufficient, we present both an exact, but time-consuming method, and a fast approximation method based on fitting distributions on the first two moments. This approximation method shows very small differences when compared to the exact method. Finally, we compare both methods to a simulation model in order to test the validity and impact of our modelling. © 2010 Elsevier Ltd. All rights reserved.

Contains fulltext : 95127.pdf (Publisher’s version ) (Closed access) A distinctive tradition within group decision support uses models to structure managerial problems. In this tradition, stakeholders jointly construct a model on their issue of concern in facilitated workshops. In the past decades a wide variety of theoretical insights into and techniques for model-based decision support have been proposed and tested in practical applications. Methods are designed and used by experts; guidelines on their use are not completely spelled out in the literature. This lack of transparency may lead to difficulties in showing the value of methods to researchers in other fields, limit transferability of methods and complicate recombining elements of methods into a multimethodology. In this paper we aim to contribute to transparency by contrasting two model-driven methods: group model building (GMB) and Strategic Options Development and Analysis (SODA). We first develop a framework for comparing methods on a theoretical and practical level. Second, we describe the separate use of each approach, on one and the same issue, with a similar group of participants. By contrasting the choices made in a practical application we clarify process and results in different phases of problem analysis. Our conclusion is that theoretical assumptions of both approaches are more similar than expected. Each method captures different aspects of the problem and in this sense methods may supplement one another: where SODA focuses on the future and identification of actions, GMB aims to create insight into the relation between (past) behavior and structure of the problem. In choosing which element of the methods to use, it is important to realize that each element strikes a particular balance between costs (e.g. time taken from participants or modelers) and benefits (e.g. level of involvement or model verification). For instance, some elements speed up the process but do so at the cost of lowering participants’ involvement. A practical combination of elements of GMB and SODA thus requires the user to assess the relative importance of insight and action as project deliverables, weigh costs and benefits of elements of either method and string these together in a logical sequence that creates the outcomes required. 19 p.

De diversiteit aan methoden en middelen waarover een commandant beschikt is de afgelopen jaren sterk toegenomen. Om deze middelen effectief in te kunnen zetten moet hij zoveel mogelijk inzicht hebben in alle factoren en actoren van invloed, waarvoor de werkmethode Intelligence Preparation of the Environment (IPE) ontwikkeld is. De Method to Analyze Relations Between Variables using Enriched Loops (MARVEL) geeft de in het IPE gebruikte causale diagrammen een extra kwantitatieve dimensie. Getoetst aan de casus van de rebellenbeweging FARC in Colombia toont MARVEL een meerwaarde bij het kunnen visualiseren en doorgronden van de dynamieken en complexiteiten van een missiegebied.

Onlangs heeft minister Hennis-Plasschaert het belang aangekaart van het vervangen van de Walrus-klasse onderzeeboot. De minister onderkent in haar visie dat de onderzeeboot zeer geschikt is voor het verzamelen, analyseren en delen van inlichtingen. Dit artikel gaat in op de inlichtingentaak van de Nederlandse onderzeeboot. Uit onderzoek blijkt dat de huidige configuratie en ondersteuning van de organisatie niet meer aansluiten bij de taken en missiegebieden. Om succesvol te zijn moet Defensie investeren in materiaal en nieuwe onderzeeboten, maar ook in personeel en opleidingen. Vooral als het gaat om het verzamelen van inlichtingen.

Social Media (SM) is a relatively new phenomenon. Intelligence agencies have been struggling to understand how to exploit the social pulse that flows from this source. The paper starts with a brief overview of SM with some examples of how it is being used by adversaries and how we might be able to exploit this usage. Often treated as another form of open source intelligence (OSINT), we look at some of the differences with traditional OSINT compared to SM then outline the possible uses by military intelligence. The next section looks at how SM fits into the different phases of the intelligence cycle: Direction, Collection, Processing and Dissemination. For the first phase, Direction, a number of questions are identified that can be answered typically by SM. For the second phase, the Collection, it is explained how SM, as an asset, transfers questions into methods and the use of different SM resources (e.g. marketer, cognitive behavioral psychologist) and sources to seek the required information. SM is exploited as a multi-intelligence capability. For the Processing phase some aspects are described in how to deal with this capacity (e.g. enabling other intelligence sources) and also which techniques are used to be able to validate the SM sources used. © 2016 SPIE.

Social Media (SM) is a relatively new phenomenon. Intelligence agencies have been struggling to understand how to exploit the social pulse that flows from this source. The paper starts with a brief overview of SM with some examples of how it is being used by adversaries and how we might be able to exploit this usage. Often treated as another form of open source intelligence (OSINT), we look at some of the differences with traditional OSINT compared to SM then outline the possible uses by military intelligence. The next section looks at how SM fits into the different phases of the intelligence cycle: Direction, Collection, Processing and Dissemination. For the first phase, Direction, a number of questions are identified that can be answered typically by SM. For the second phase, the Collection, it is explained how SM, as an asset, transfers questions into methods and the use of different SM resources (e.g. marketer, cognitive behavioral psychologist) and sources to seek the required information. SM is exploited as a multi-intelligence capability. For the Processing phase some aspects are described in how to deal with this capacity (e.g. enabling other intelligence sources) and also which techniques are used to be able to validate the SM sources used. © 2016 SPIE.

Onlangs heeft minister Hennis-Plasschaert het belang aangekaart van het vervangen van de Walrus-klasse onderzeeboot. De minister onderkent in haar visie dat de onderzeeboot zeer geschikt is voor het verzamelen, analyseren en delen van inlichtingen. Dit artikel gaat in op de inlichtingentaak van de Nederlandse onderzeeboot. Uit onderzoek blijkt dat de huidige configuratie en ondersteuning van de organisatie niet meer aansluiten bij de taken en missiegebieden. Om succesvol te zijn moet Defensie investeren in materiaal en nieuwe onderzeeboten, maar ook in personeel en opleidingen. Vooral als het gaat om het verzamelen van inlichtingen.

De diversiteit aan methoden en middelen waarover een commandant beschikt is de afgelopen jaren sterk toegenomen. Om deze middelen effectief in te kunnen zetten moet hij zoveel mogelijk inzicht hebben in alle factoren en actoren van invloed, waarvoor de werkmethode Intelligence Preparation of the Environment (IPE) ontwikkeld is. De Method to Analyze Relations Between Variables using Enriched Loops (MARVEL) geeft de in het IPE gebruikte causale diagrammen een extra kwantitatieve dimensie. Getoetst aan de casus van de rebellenbeweging FARC in Colombia toont MARVEL een meerwaarde bij het kunnen visualiseren en doorgronden van de dynamieken en complexiteiten van een missiegebied.

In the last decades we witnessed the creation of a virtual world: cyberspace, which offers plenty of opportunities and challenges. Meanwhile, we are confronted with many conflict situations between different groups of people or countries. In the last years, several events have been described in terms of cyber warfare or the use of cyber weapons, leading to critical international security concerns. At the same time, there is little research on the definitions of what constitutes a cyber weapon and how it can be profiled.The present article gives an answer to the question “How to define cyber weapons?” and proposes a conceptual framework that defines and profiles cyber weapons from a multidisciplinary perspective: cyber and military, considering legal aspects as well. This framework establishes the context of use and the life cycle of cyber weapons, defines them, presents their structure and proposes a way to profile them. The aim of this article is to support decision makers and academia that have to deal with the implications and consequences of cyber weapons. Therefore, to evaluate our framework, we propose a profiling matrix for Stuxnet, Operation Orchard and Black Energy and we conduct an exploratory case study on Stuxnet based on the existing literature and reports. We conclude by presenting our future research.

Research has shown that many individuals have difficulties solving tasks that involve a principal component of dynamic systems: accumulation. They incorrectly assume that the behavioural pattern of a stock resembles that of its flows and vice versa. This has become known as correlation heuristic reasoning.Much less is known about the underlying causes of this inability to correctly infer dynamic behaviour from graphs. We tested if two dimensions of spatial ability, spatial visualization and spatial relations, are related to selecting correct or correlation heuristic answers in tasks involving graphs over time. The analyses show that spatial visualization is positively related to performance in some systems thinking inventory tasks and is negatively related to responses that show correlation heuristic reasoning. We conclude by discussing avenues for future research into this phenomenon.

In the last decades we witnessed the creation of a virtual world: cyberspace, which offers plenty of opportunities and challenges. Meanwhile, we are confronted with many conflict situations between different groups of people or countries. In the last years, several events have been described in terms of cyber warfare or the use of cyber weapons, leading to critical international security concerns. At the same time, there is little research on the definitions of what constitutes a cyber weapon and how it can be profiled.The present article gives an answer to the question “How to define cyber weapons?” and proposes a conceptual framework that defines and profiles cyber weapons from a multidisciplinary perspective: cyber and military, considering legal aspects as well. This framework establishes the context of use and the life cycle of cyber weapons, defines them, presents their structure and proposes a way to profile them. The aim of this article is to support decision makers and academia that have to deal with the implications and consequences of cyber weapons. Therefore, to evaluate our framework, we propose a profiling matrix for Stuxnet, Operation Orchard and Black Energy and we conduct an exploratory case study on Stuxnet based on the existing literature and reports. We conclude by presenting our future research.

Mismanagement of societal aging is an important threat to health care, social security, and the economy of many nations. A System Dynamics simulation model related to societal aging in the Netherlands and its implications for the Dutch welfare system is used here to generate exploratory scenarios and to test policy robustness across many scenarios. Key concerns derived from this research are (i) the existence of plausible scenarios with severe labor scarcity, especially in health care, (ii) unsustainable evolutions of health care costs, and (iii) insufficient labor productivity, especially in health care. The authors’ analysis shows that labor productivity may be cause of, and cure for, many of undesirable evolutions. The authors conclude that there is a need for: (i) sufficient increases in labor productivity, especially in health care, without pinching the necessary workers in care, and (ii) sufficiently raising the retirement age as well as raising the willingness to work longer and to employ older people. These conclusions are derived from the systematic data analysis documented in the appendix.

Contains fulltext : 162275pub.pdf (Publisher’s version ) (Closed access) When faced with wicked and messy problems, practitioners can rely on a variety of problem structuring methods (PSMs). Although previous efforts have been made to combine such methods with simulation, currently, few exist that integrate a simulation capability within problem structuring. Our integrated approach named MARVEL (method to analyse relations between variables using enriched loops) shares some techniques with established methods such as the PSM SODA (strategic options development and analysis), system dynamics, and fuzzy cognitive maps. In addition, MARVEL uses causal loop diagrams that are enriched with qualitatively labelled values and standardized equations. This makes analyses of both model structure and behaviour possible. MARVEL also maintains the benefits of a PSM, such as being cognitively accessible for a wide variety of actors. The current paper presents MARVEL in technical terms, and discusses the similarities and differences it has with the aforementioned methods. We then present a case study that discusses how MARVEL was used in a collaborative setting to facilitate stakeholders’ assessment of tactical military actions during stabilization operations.

When faced with wicked and messy problems, practitioners can rely on a variety of problem structuring methods (PSMs). Although previous efforts have been made to combine such methods with simulation, currently, few exist that integrate a simulation capability within problem structuring. Our integrated approach named MARVEL (method to analyse relations between variables using enriched loops) shares some techniques with established methods such as the PSM SODA (strategic options development and analysis), system dynamics, and fuzzy cognitive maps. In addition, MARVEL uses causal loop diagrams that are enriched with qualitatively labelled values and standardized equations. This makes analyses of both model structure and behaviour possible. MARVEL also maintains the benefits of a PSM, such as being cognitively accessible for a wide variety of actors. The current paper presents MARVEL in technical terms, and discusses the similarities and differences it has with the aforementioned methods. We then present a case study that discusses how MARVEL was used in a collaborative setting to facilitate stakeholders’ assessment of tactical military actions during stabilization operations.

Mismanagement of societal aging is an important threat to health care, social security, and the economy of many nations. A System Dynamics simulation model related to societal aging in the Netherlands and its implications for the Dutch welfare system is used here to generate exploratory scenarios and to test policy robustness across many scenarios. Key concerns derived from this research are (i) the existence of plausible scenarios with severe labor scarcity, especially in health care, (ii) unsustainable evolutions of health care costs, and (iii) insufficient labor productivity, especially in health care. The authors’ analysis shows that labor productivity may be cause of, and cure for, many of undesirable evolutions. The authors conclude that there is a need for: (i) sufficient increases in labor productivity, especially in health care, without pinching the necessary workers in care, and (ii) sufficiently raising the retirement age as well as raising the willingness to work longer and to employ older people. These conclusions are derived from the systematic data analysis documented in the appendix.

In veel maritieme operaties vormt het proces van oppervlaktebeeldopbouw een belangrijke component. Door middel van simulatle is het mogelijk dit proces te verbeteren en daarmee de operationele effectiviteit van een maritieme operatie te verhogen. Daarom heeft de afdeling Military Operations van TNO een simulatiemodel voor maritieme oppervlaktebeeldopbouw ontwikkeld: SURPASS (afkorting van SURface Picture ASSessment). In dit model zijn de aspecten van maritieme oppervlakte beeldopbouw in detail gemodelleerd. Het doel van simulatie met SURPASS is het verkrijgen van inzicht In de effecten van verschillende middelen voor beeldopbouw en van verschillende gebruikte tactieken. Met dit artikel beogen de auteurs het model en zijn toepassingsmogeljkheden bekend te stellen.

Unmanned Aerial Vehicles (UAVs) are important assets for information gathering in Intelligence Surveillance and Reconnaissance (ISR) missions. Depending on the uncertainty in the planning parameters, the complexity of the mission and its constraints and requirements, different planning methods might be preferred. The first two planning approaches that we will discuss, deal with uncertainty in fuel consumption of the UAV. The third planning approach is designed for an even more uncertain and dynamic situation in which travel and recording times are stochastic, time windows are associated to target locations and new targets become of interest during the flight of the UAV. As such, the proposed approaches gradually move from robust to agile as the uncertainty and dynamicity in the problems increases.

Het aantal vermissingen is de laatste jaren steeds toegenomen, volgens Landelijk Bureau Vermiste Personen (De Telegraaf 2014), en het hoge aantal vereist een grote politie-inspanning. Het efficiënt en effectief aanpakken van een vermissing wordt dus alleen maar belangrijker. Dit artikel gaat in op de huidige werkwijze en problematiek bij vermissingsopsporing en introduceert een in Nederland ontwikkelde methodiek, het HMF-vermissingsmodel

Unmanned Aerial Vehicles (UAVs) are important assets for information gathering in Intelligence Surveillance and Reconnaissance (ISR) missions. Depending on the uncertainty in the planning parameters, the complexity of the mission and its constraints and requirements, different planning methods might be preferred. The first two planning approaches that we will discuss, deal with uncertainty in fuel consumption of the UAV. The third planning approach is designed for an even more uncertain and dynamic situation in which travel and recording times are stochastic, time windows are associated to target locations and new targets become of interest during the flight of the UAV. As such, the proposed approaches gradually move from robust to agile as the uncertainty and dynamicity in the problems increases.

De Nederlandse krijgsmacht heeft in 2012 een Cyber Strategie1 opgesteld. In deze strategie wordt de ambitie uitgesproken om de komende jaren de digitale weerbaarheid te versterken en het vermogen te ontwikkelen om offensieve cyberoperaties uit te voeren met als doel de inzetbaarheid van de krijgsmacht te waarborgen en haar effectiviteit te verhogen. Met een dergelijk cybervermogen heeft een commandant een nieuwe effectenbrenger ter beschikking. Maar hoe zet je zo’n digitaal vermogen, in samenhang met andere vermogens, in?

In veel maritieme operaties vormt het proces van oppervlaktebeeldopbouw een belangrijke component. Door middel van simulatle is het mogelijk dit proces te verbeteren en daarmee de operationele effectiviteit van een maritieme operatie te verhogen. Daarom heeft de afdeling Military Operations van TNO een simulatiemodel voor maritieme oppervlaktebeeldopbouw ontwikkeld: SURPASS (afkorting van SURface Picture ASSessment). In dit model zijn de aspecten van maritieme oppervlakte beeldopbouw in detail gemodelleerd. Het doel van simulatie met SURPASS is het verkrijgen van inzicht In de effecten van verschillende middelen voor beeldopbouw en van verschillende gebruikte tactieken. Met dit artikel beogen de auteurs het model en zijn toepassingsmogeljkheden bekend te stellen.

Het aantal vermissingen is de laatste jaren steeds toegenomen, volgens Landelijk Bureau Vermiste Personen (De Telegraaf 2014), en het hoge aantal vereist een grote politie-inspanning. Het efficiënt en effectief aanpakken van een vermissing wordt dus alleen maar belangrijker. Dit artikel gaat in op de huidige werkwijze en problematiek bij vermissingsopsporing en introduceert een in Nederland ontwikkelde methodiek, het HMF-vermissingsmodel

De Nederlandse krijgsmacht heeft in 2012 een Cyber Strategie1 opgesteld. In deze strategie wordt de ambitie uitgesproken om de komende jaren de digitale weerbaarheid te versterken en het vermogen te ontwikkelen om offensieve cyberoperaties uit te voeren met als doel de inzetbaarheid van de krijgsmacht te waarborgen en haar effectiviteit te verhogen. Met een dergelijk cybervermogen heeft een commandant een nieuwe effectenbrenger ter beschikking. Maar hoe zet je zo’n digitaal vermogen, in samenhang met andere vermogens, in?

Military intelligence communities need to collect, process and disseminate information as quickly and efficiently as possible, for example in answering requests for information by commanders. Currently, the flow of information between the field and intelligence communities is hampered by disparities in the integration of the various components of the information chain. We propose to create a hub for information exchange called SOPHIE, where information from heterogeneous sources comes together. This hub proactively notifies military users to relevant information based on their profile. In addition, users can search or browse available information products and consult experts to receive quick answers to their information requests. © Springer International Publishing Switzerland 2014.

Stel dat we toekomstige systemen nu al konden beproeven? Zou het niet fantastisch zijn als we de benodigde capaciteiten voor militairen snel en goedkoop konden realiseren en de tijdens missies opgedane ervaringen gemakkelijk en spelenderwijs met elkaar konden delen? ’Concept Development & Experimentation’ (CD&E) kan een belangrijke sleutel zijn om deze fantasieën mogelijk te maken. Dit artikel gaat in op de betekenis van CD&E en zal een aanzet geven hoe CD&E een essentiële katalysator kan zijn voor belangrijke processen binnen het defensiedomein. Daarbij komt tevens aan bod op welke manier CD&E kan helpen bij het realiseren van betaalbare en effectieve capaciteiten (‘capabilities’) voor de krijgsmacht.

Unmanned Aerial Vehicles (UAVs) can provide significant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specific target locations within the area of interest. In order to improve the effectiveness of a reconnaissance mission, it is important to visit the largest number of interesting target locations possible, taking into consideration operational constraints related to fuel usage between target locations, weather conditions and endurance of the UAV. We model this planning problem as the well-known orienteering problem, which is a generalization of the traveling salesman problem. Given the uncertainty in the military operational environment, robust planning solutions are required. Therefore our model takes into account uncertainty in the fuel usage between targets, for instance due to weather conditions. We report results using different uncertainty sets that specify the degree of uncertainty against which any feasible solution will be protected. We also compare the probability that a solution is feasible for the robust solution on one hand and the solution found with average fuel usage on the other. These probabilities are assessed both by simulation and by derivation of problem specific theoretical bounds on the probability of constraint feasibility. In doing so, we show how the sustainability of a UAV mission can be significantly improved. Additionally, we suggest how the robust solution can be operationalized in a realistic setting, by complementing the robust tour with agility principles

Dit artikel bespreekt de samenhang tussen de werkvelden van fysieke en sociale veiligheid. Op basis van resultaten van een onderzoeksproject over multidisciplinaire samenwerking en informatiedeling in het veiligheidsdomein in Nederland beargumenteren we dat het niet realistisch is om te spreken van twee onafhankelijke werkvelden, maar dat het zinvoller is om te spreken over één veiligheidsdomein waarbinnen situaties van onveiligheid vanuit een breder (fysiek én sociaal) perspectief worden bekeken. In het artikel bespreken we de mogelijkheden die wij zien om de werkvelden van fysieke en sociale veiligheid beter op elkaar te laten aansluiten.

Type II Diabetes Mellitus is one of the fastest growing chronic diseases in the western world. This exploratory research provides an insight into the causes for the diabetes prevalence in The Netherlands by performing an Exploratory Modelling and Analysis (EMA) study on an adaptation of an existing macrolevel diabetes System Dynamics model. The model used is adapted from the diabetes model by Jones et al. (2006) and a number of policies that are currently considered to be implemented are tested. The analysis shows that high numbers of diabetes patients are caused by high levels of risk of (pre)diabetes for certain groups and diabetes and prediabetes onset. Recommended is more research into narrowing the uncertainty bandwidth of these parameters or to monitor these parameters in Dutch society. The policies as currently proposed, where high risk groups for having prediabetes are determined via a questionnaire and prediabetes patients are offered lifestyle interventions do not have considerable effect. By making these interventions less non-committed, effects of the policy increases considerably in terms of number of diabetes patients and costs, but it requires testing a much larger part of the risk group. Researching whether these high attendances of risk groups should be further researched.

The complexity and dynamics of current military operations demand reliable and up-to-date intelligence and in particular near-real-time threat assessment. This paper explores the potential of operational analysis techniques in supporting military personnel in processing information from different sources, in order to constantly carry out near-real time threat assessments of current situations and future developments. It introduces a near-real time threat assessment approach that integrates Bayesian Belief Networks and spatio-temporal modelling. This approach has been implemented in a near-real-time intelligence demonstrator to support threat assessment during operations.

The Orienteering Problem (OP) is a routing problem which has many interesting applications in logistics, tourism and defense. The aim of the OP is to find a maximum profit path or tour, which is feasible with respect to a capacity constraint on the total weight of the selected arcs. In this paper we consider the Orienteering Problem with Stochastic Weights (OPSW) to reflect uncertainty in real-life applications. We approach this problem by formulating a two-stage stochastic model with recourse for the OPSW where the capacity constraint is hard. The model takes into account the effect that stochastic weights have on the expected total profit value to be obtained, already in the modeling stage. Since the expected profit is in general non-linear, we introduce a linearization that models the total profit that can be obtained for a given tour and a given scenario of weight realizations. This linearization allows for the application of Sample Average Approximation (SAA). The SAA solution asymptotically converges to the optimal solution of the two-stage model, but is computationally expensive. Therefore, to solve large instances, we developed a heuristic that exploits the problem structure of the OPSW and explicitly takes the associated uncertainty into account. In our computational experiments, we evaluate the benefits of our approach to the OPSW, compared to both a standard deterministic approach, and a deterministic approach that is extended with utilization of real-time information.

The concept of the ‘Smart City’ is seen as double edged sword that should alleviate societal and environmental problems as well as fuel economic growth. Literature has identified many important characteristics of Smart Cities but has not yet provided a systemic approach that describes the interdependencies between these characteristics. The current study was conducted in support of an integrated approach for developing Smart City initiatives. We used group model building and interviews together with the MARVEL method to describe the interrelations between People, Environment, Living condition, Governance, Economy and Mobility. MARVEL is a method and a tool for developing CLD like causal models. The model forms the basis for a systemic framework to supports diverse sets of stakeholders in the development and analysis of future smart city initiatives. We demonstrate how various functions of MARVEL can be used to perform qualitative analysis to this end.

Unmanned Aerial Vehicles (UAVs) have become an essential asset for military and law enforcement operations. In particular their use for surveillance and reconnaissance tasks has been growing due to the quick developments in the areal systems themselves, sensor technology, and image processing techniques that enable near-realtime acquisition of information about activities and/or emergent situations in areas of interest. However, collecting information from all the required locations often is not possible due to the endurance of the UAV. This chapter will address the online UAV planning problem wherein operators have to plan UAV missions in the most efficient way based on available information on the performance of the UAV and additional requests for information

The complexity and dynamics of current military operations demand reliable and up-to-date intelligence and in particular near-real-time threat assessment. This paper explores the potential of operational analysis techniques in supporting military personnel in processing information from different sources, in order to constantly carry out near-real time threat assessments of current situations and future developments. It introduces a near-real time threat assessment approach that integrates Bayesian Belief Networks and spatio-temporal modelling. This approach has been implemented in a near-real-time intelligence demonstrator to support threat assessment during operations.

When groups of consumers share information or express their opinions about products and services, their attitudes or behavior sometime align without centralized coordination, a phenomenon known as herding. Building on pattern-based explanations of herding from the cognitive science literature, we propose a framework to elucidate herding behavior based on three dimensions: the speed of contagion, i.e., the extent to which the behavior spreads in a given time, the number of individuals, i.e., the proportion of the whole population expressing the behavior, and the uniformity of direction, i.e., the extent to which the mass behavior is increasingly uniform with one variant becoming dominant. Based on these dimensions, we differentiate eight patterns of herding behavior from slowly diffusing, small and disparate groups through to rapidly spreading, massive herds expressing a convergent behavior. We explore these herding patterns in an online setting, measuring their prevalence using over four thousand streams of data from the online micro-blogging application, Twitter. We find that all eight patterns occur in the empirical data set although some patterns are rare, particularly those where a convergent behavior rapidly spreads through the population. Importantly, those occurrences that develop into the pattern we call "stampeding," i.e., the rapid spread of a dominant opinion expressed by many people, generally follow a consistent development path. The proposed framework can help managers to identify such noteworthy herds in real time, and represents a first step in anticipating this form of group behavior. © 2013 .

When groups of consumers share information or express their opinions about products and services, their attitudes or behavior sometime align without centralized coordination, a phenomenon known as herding. Building on pattern-based explanations of herding from the cognitive science literature, we propose a framework to elucidate herding behavior based on three dimensions: the speed of contagion, i.e., the extent to which the behavior spreads in a given time, the number of individuals, i.e., the proportion of the whole population expressing the behavior, and the uniformity of direction, i.e., the extent to which the mass behavior is increasingly uniform with one variant becoming dominant. Based on these dimensions, we differentiate eight patterns of herding behavior from slowly diffusing, small and disparate groups through to rapidly spreading, massive herds expressing a convergent behavior. We explore these herding patterns in an online setting, measuring their prevalence using over four thousand streams of data from the online micro-blogging application, Twitter. We find that all eight patterns occur in the empirical data set although some patterns are rare, particularly those where a convergent behavior rapidly spreads through the population. Importantly, those occurrences that develop into the pattern we call "stampeding," i.e., the rapid spread of a dominant opinion expressed by many people, generally follow a consistent development path. The proposed framework can help managers to identify such noteworthy herds in real time, and represents a first step in anticipating this form of group behavior. © 2013 .

The concept of the ‘Smart City’ is seen as double edged sword that should alleviate societal and environmental problems as well as fuel economic growth. Literature has identified many important characteristics of Smart Cities but has not yet provided a systemic approach that describes the interdependencies between these characteristics. The current study was conducted in support of an integrated approach for developing Smart City initiatives. We used group model building and interviews together with the MARVEL method to describe the interrelations between People, Environment, Living condition, Governance, Economy and Mobility. MARVEL is a method and a tool for developing CLD like causal models. The model forms the basis for a systemic framework to supports diverse sets of stakeholders in the development and analysis of future smart city initiatives. We demonstrate how various functions of MARVEL can be used to perform qualitative analysis to this end.