Constrained Node Placement and Assignment in Mobile Backbone Networks

This paper describes new algorithms for mobile backbone network optimization. In this hierarchical communication framework, mobile backbone nodes (MBNs) are deployed to provide communication support for regular nodes (RNs). While previous work has assumed that MBNs are unconstrained in position, this work models constraints in MBN location. This paper develops an exact technique for maximizing the number of RNs that achieve a threshold throughput level, as well as a polynomial-time approximation algorithm for this problem. The approximation algorithm carries a performance guarantee of 12, and we demonstrate that this guarantee is tight in some problem instances

Integrated Supply- and Demand-Side Energy Management for Expeditionary Environmental Control

PreprintThis paper examines efficiencies achieved by optimal scheduling of power generation equipment and electrical loads in a hybrid smart micro-grid under conditions where load activity may be delayed or advanced with negligible impact to system performance. We model military expeditionary energy systems to analyze the performance of existing unmanaged components and estimate potential savings obtained by coordinated management of battlefield heating and cooling systems. We employ rolling horizon optimization models to examine performance under varying degrees of uncertainty about future load demand and renewable production. We propose a novel mechanism to reduce power production costs through optimal prescriptive scheduling of loads, reducing peak demand and generator peak-to-average power ratios and facilitating a persistent shift to higher fuel efficiencies. In contrast to existing methods that employ either supply-side or demand-side management, we propose intelligently coordinating both sides to achieve greater efficiency. Using sensitivity analysis, this paper quantitatively demonstrates how grid composition, temperature band tolerance, and energy storage capabilities contribute to fuel efficiency under this approac

Pricing contracts under uncertainty in a carbon capture and storage framework

The article of record may be found at http://dx.doi.org/10.1016/j.eneco.2014.02.003Carbon capture and storage (CCS) has been demonstrated as a viable option for reducing carbon emissions to the atmosphere. We consider a situation where a tax on emissions is imposed on carbon dioxide (CO2) producers to encourage their participation in CCS. Operators of CO2 transportation pipelines and storage sites enter into individual contracts with emissions producers to store CO2. We study the problem of selecting the optimal price andvolume of these contracts under both cost and emissions uncertainty to optimize the storage operator's expected profit

A Method for Placing Sources in Multistatic Sonar Networks

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