Maximizing Expected Coverage of Flow and Opportunity for Diversion in Networked Systems

Placement of facilities, such as those providing surveillance or assistance functions, is essential for effective and efficient system operation. Planning for where to provide these types of services in a network necessitates addressing different objectives. For instance, notifying users of future network conditions and/or availability of other services requires general exposure to that information at some point during a movement between an origin and destination. Alternatively, the usefulness of services such as the provision of information regarding current network conditions can depend upon where the service is provided relative to opportunities for users to divert from their current path to make use of that service. Regardless of the service to be made available, there is always some uncertainty as to whether or not it will be available and/or observed by users of the system. To address these planning considerations, several new models for optimizing the location of service facilities in a network are described. In particular, the proposed models account for expected coverage of network flows as well as the opportunity that exists for flows to make effective use of a service once it has been provided. While the proposed models involve non-linear objective functions, it is shown that a linearization exists given the topological relationships within a network. The developed optimization models are then integrated into a multi-objective modeling framework and applied to a case study to demonstrate the tradeoffs that exist between the planning objectives.

     

Change of Scene: The Geographic Dynamics of Resilience to Vehicular Accidents

Networks and Spatial Economics - Most have experienced the impact of vehicular accidents, whether it was in terms of increased commute time, delays in receiving goods, higher insurance premiums,...     

Strategic Network Restoration

For any networked infrastructure, damage to arcs and/or nodes and associated disruption of network services is inevitable. To reestablish service in a damaged network, affected components must be repaired or reconfigured, a process that can be time consuming and costly, so care must be taken to identify network restoration strategies that reestablish service most efficiently. A strategic goal of service restoration, therefore, is to ensure that facility restoration is prioritized so that system performance is maximized over a planning horizon within budgetary restrictions. To address this problem, this paper proposes a multi-objective optimization approach for network restoration during disaster recovery. The proposed model permits tradeoffs between two objectives, minimization of system cost and maximization of system flow, to be evaluated. A telecommunication application illustrates the significance of the developed approach.     

Exploring the vulnerability of network infrastructure to disruption

Disruption of network facilities (nodes or arcs) resulting in loss of system functionality is of particular concern in the operation of critical network infrastructures. In preparing for events such as natural disasters, accidents, and/or sabotage, numerous disruption possibilities exist for any network and efforts to safeguard against the most destructive of those are often sought. Although, many approaches exist for identifying network vulnerabilities, mathematical programming and simulation are typically used as exploratory approaches for uncovering potentially important disruption scenarios. Mathematical programming approaches can identify bounds on network vulnerability while simulation can provide important insights to complement these bounds, as well as provide insights in cases where mathematical programming is not practical. This research presents a simulation methodology for evaluating network vulnerability to disruption. A case study illustrates the complexities associated with planning for such events.