907 research outputs found

    Optimal Interdiction of Unreactive Markovian Evaders

    Full text link
    The interdiction problem arises in a variety of areas including military logistics, infectious disease control, and counter-terrorism. In the typical formulation of network interdiction, the task of the interdictor is to find a set of edges in a weighted network such that the removal of those edges would maximally increase the cost to an evader of traveling on a path through the network. Our work is motivated by cases in which the evader has incomplete information about the network or lacks planning time or computational power, e.g. when authorities set up roadblocks to catch bank robbers, the criminals do not know all the roadblock locations or the best path to use for their escape. We introduce a model of network interdiction in which the motion of one or more evaders is described by Markov processes and the evaders are assumed not to react to interdiction decisions. The interdiction objective is to find an edge set of size B, that maximizes the probability of capturing the evaders. We prove that similar to the standard least-cost formulation for deterministic motion this interdiction problem is also NP-hard. But unlike that problem our interdiction problem is submodular and the optimal solution can be approximated within 1-1/e using a greedy algorithm. Additionally, we exploit submodularity through a priority evaluation strategy that eliminates the linear complexity scaling in the number of network edges and speeds up the solution by orders of magnitude. Taken together the results bring closer the goal of finding realistic solutions to the interdiction problem on global-scale networks.Comment: Accepted at the Sixth International Conference on integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2009

    A bi-level model and solution methods for partial interdiction problem on capacitated hierarchical facilities

    Get PDF
    Due to the importance of gaining high levels of customer satisfaction in today's competitive world, making appropriate decisions in the face of malicious attacks is valued highly by many organizations. In this paper, to predict and handle the destructive effects of an intentional attack on capacitated nested hierarchical facilities, a bi-level partial interdiction problem is proposed. In this problem, there is an interdictor who can attack facilities partially in different levels. Subsequently, the system defender could respond to the customers’ demand in two different ways, namely through the remaining system facilities and the outsourcing option. The goal of the defender is to minimize the satisfaction cost of all customers’ demand under the interdictor's attacking scenario. This problem can be modeled as a bi-level programming model in which an interdictor and the system defender play the role of the leader and the follower, respectively. Due to the inherent complexity of the bi-level programming models, we develop a heuristic approach, namely “FDS”, to obtain near optimal solutions within a reasonable running time. In each iteration of the FDS, an interdiction scenario is produced heuristically and, thereupon CPLEX solver is called to solve the lower level of the model. To evaluate the effectiveness of the proposed model, a comparison between the cost of customers’ demand satisfaction in both absence and presence of the bi-level model is drawn. Computational results show that for those instances in which the optimal solutions are available, the proposed model can, on average, achieve a saving of 7.94%

    Problem solving with geographic networks in the Sacramento-San Joaquin Delta

    Get PDF
    The Sacramento-San Joaquin Delta (Delta) serves as the crossroads for many geographic networks that crisscross California. These include a conveyance network for drinking water, a biological network for delta smelt, and a transportation network for roads. As a result, local Delta issues concerning flooding and endangered fish hold implications for the entire state. This thesis explores these underlying network structures that pass through the Delta as a means for solving subsets of these most difficult challenges. Recognition of these larger networks enable the transformation of the Delta\u27s convoluted maze of waterways and islands into a series of nodes and segments. Network principles of backup routes, shortest paths, and busiest intersections are applied to uniquely Delta problems resulting in lists for potentially stranded islands, optimal monitoring sites for delta smelt, and select paths for levee fortification. This thesis concludes that networks can be a versatile tool not only for the Delta but wherever networks exist. Especially with increasing clashes between people and nature, networks offer a way to connect seemingly disparate problems with solutions in the form of specific locations that establishes the starting point for stakeholders to work towards a compromise

    Mexican drug cartels and their Australian connections: tracking and disrupting dark networks

    Get PDF
    For Australia, the emergence of Mexican drug cartels presents significant policymaking, intelligence and strategic challenges. The size of these operations, their resource base and the fluid nature of dark network structures makes these enterprise syndicates a highly versatile and resilient opponent. This paper will provide an analysis of the organisational levels of dark networks in dealing with Mexican drug cartels and explores how these profit-seeking transnational actors form and operate including their motivations and modus operandi. It will also address the problematic nature of dark networks and the importance of robust intelligence collection and analysis capabilities to better prioritise border protection responses as well as to increase the ability of the security sector to target dispersed ‘webs’ of illicit affiliations, with a focus on the Asia-Pacific region

    Analytical approaches to protection planning in rail-truck intermodal transportation

    Get PDF
    A significant volume of traffic uses a rail-truck intermodal transportation network, making it the preferred transportation medium for customers. Thus, the associated infrastructure of rail-truck intermodal transportation should be considered critical, i.e., systems and assets whose destruction (or disruption) would have a crippling effect on security, economy, public health, and safety. Disruptions could be induced by nature such as hurricane Katrina in 2005, or man-made disturbances such as the 9/11 terrorist attacks in the United States. This thesis proposes an analytical approach to preserve, as much as possible, the functionality of a rail-truck intermodal transportation system in the wake of worst-case attacks. As such, it will serves as an aid to the top managers to compare the cost of implementing protective measures with the benefits that such measures could bring. A tri-level Defender-Attacker-Defender (DAD) approach is proposed to model this situation, where the outermost problem belongs to the network operator with a limited budget to protect some of the terminals, the middle level problem belongs to the attacker with enough resources to interdict some of the un-protected terminals, and the innermost problem belongs to the intermodal operator who attempts to meet the demand on a reduced network with the minimum cost. Since the resulting model is very difficult to solve by any optimization package, efficient solution techniques have been developed for solving this model. Finally, the proposed framework is applied to the rail-truck intermodal transportation network of a Class I railroad operator in North America to discover the optimal way to protect the system

    Optimizing Distribution Sensor Placement for Border Patrol Interdiction using Microsoft Excel

    Get PDF
    The purpose of this research was to develop an electronic sensor placement model for border security. A model was developed using Microsoft Excel, with some add-on capabilities, to optimize the placement of electronic sensors on a border network given a pre-determined budgetary constraint. The model is capable of handling multiple sensor types, which are placed together as packages, and allows for daytime, nighttime, or 24 hour operation of each sensor type. Additionally, each sensor can be assigned a specific range and detection probability curve within the given range. The model is capable of optimizing either average coverage, or minimum coverage, across the nodes of a network by selecting the nodes where sensor packages are to be placed. Due to its simplicity and ability to run in Microsoft Excel, it is believed that the model developed in this research can also be used in a number of military applications where border security is necessary

    Autonomous aircraft initiative study

    Get PDF
    The results of a consulting effort to aid NASA Ames-Dryden in defining a new initiative in aircraft automation are described. The initiative described is a multi-year, multi-center technology development and flight demonstration program. The initiative features the further development of technologies in aircraft automation already being pursued at multiple NASA centers and Department of Defense (DoD) research and Development (R and D) facilities. The proposed initiative involves the development of technologies in intelligent systems, guidance, control, software development, airborne computing, navigation, communications, sensors, unmanned vehicles, and air traffic control. It involves the integration and implementation of these technologies to the extent necessary to conduct selected and incremental flight demonstrations
    • 

    corecore