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Electoral economics: Maximizing local representation under proportionality

ECONOMICS LETTERS 2019年 182卷 109-113页

作者： Antweiler, Werner Univ British Columbia Sauder Sch Business 2053 Main Mall Vancouver BC V6T 1Z2 Canada

Electoral systems struggle to combine proportionality (fair representation) and direct accountability (local representation). Economic optimization tools can be used to devise an improvement to conventional forms of proportional representation. Single or dual optimal assignment of constituencies can provide better local representation by maximizing the number of voters who are represented directly. (C) 2019 The Author. Published by Elsevier B.V.

关键词： Elections Electoral systems Proportional representation binary integer programming

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PACTS: Power-Aware Charging Time Scheduling in Wireless Rechargeable UAV Networks

PACTS: Power-Aware Charging Time Scheduling in Wireless Rech...

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40th IEEE International Performance, Computing, and Communications Conference (IPCCC)

作者： Li, Mengqi Liu, Liang Wang, Yanlin Xi, Jie Wang, Lisong Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing Peoples R China

ISBN: (纸本)9781665443319

Recently, wireless power transmission technology (WPT) is used in wireless rechargeable unmanned aerial vehicle (UAV) networks (WRUNs) to replenish energy for UAVs. In WRUN, if UAVs cannot replenish energy in time, the task will fail or the task completion time will be greatly prolonged. So, when and how long should the wireless static chargers (WSCs) be scheduled to replenish energy for UAVs while the energy utilization rate of WSCs can be optimized is very critical. However, the existing methods only optimize the charging time periods, that is the time durations during which WSCs release energy, ignoring the impact of the adjustable source power of WSCs. In fact, inappropriate source power will lead to the low energy utilization rate of WSCs. This paper takes both the charging time periods and the adjustable source power of WSCs into account and formulates the power-aware charging time scheduling (PACTS) problem as an optimization problem. Namely, how to decide the optimal charging time periods and the appropriate source power in each charging time period simultaneously to improve the energy utilization rate of WSCs. To solve PACTS, we first discretize the flight paths of UAVs spatiotemporally and then present a novel method to reformulate PACTS as a binary integer programming (BIP) problem that can be solved by existing algorithms. Finally, experiments are conducted to evaluate the performance of our scheme.

关键词： UAV networks wireless charging UAV charging binary integer programming power-aware

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Improved Resource Allocation Algorithm Based on Partial Solution Estimation for SC-FDMA Systems

Improved Resource Allocation Algorithm Based on Partial Solu...

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IEEE 78th Vehicular Technology Conference (VTC Fall)

作者： Lei, Lei Fowler, Scott Yuan, Di Linkoping Univ Dept Sci & Technol SE-60174 Norrkoping Sweden

ISBN: (纸本)9781467361873

Single carrier frequency division multiple access (SC-FDMA) has been adopted as the standard multiple access scheme for 3GPP LTE uplink. In comparison to orthogonal frequency division multiple access (OFDMA), the subcarriers assigned to each user are required to be consecutive in SC-FDMA localized scheme, which imposes more difficulties on resource allocation problem. Subject to this constraint, various optimization objectives, such as utility maximization and power minimization, have been studied for SC-FDMA resource allocation. In this paper, we focus on developing a general algorithm framework with near-optimal performance and polynomial-time complexity to maximize the total utility for SC-FDMA systems. The proposed algorithm is based on low-complexity estimation for the partial solution space. Compared with existing algorithms, simulation results show that our algorithm improves the system utility significantly and has less deviation to global optimum. In addition, the proposed algorithm framework allows a flexible trade-off between computational effort and solution performance by varying the complexity of estimation approaches.

关键词： SC-FDMA Algorithm Resource Allocation binary integer programming Partial Solution Estimation

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Assessing the vulnerability of military theater distribution routes

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Journal of Defense Analytics and Logistics 2019年第1期3卷 60-82页

作者： Muckensturm, Joshua R. Longhorn, Dave C. Joint Distribution Process Analysis Center US Transportation Command Scott AFB IL United States

Purpose: This paper introduces a new heuristic algorithm that aims to solve the military route vulnerability problem, which involves assessing the vulnerability of military cargo flowing over roads and railways subject to enemy interdiction. Design/methodology/approach: Graph theory, a heuristic and a binary integer program are used in this paper. Findings: This work allows transportation analysts at the United States Transportation Command to identify a relatively small number of roads or railways that, if interdicted by an enemy, could disrupt the flow of military cargo within any theater of operation. Research limitations/implications: This research does not capture aspects of time, such as the reality that cargo requirements and enemy threats may fluctuate each day of the contingency. Practical implications: This work provides military logistics planners and decision-makers with a vulnerability assessment of theater distribution routes, including insights into which specific roads and railways may require protection to ensure the successful delivery of cargo from ports of debarkation to final destinations. Originality/value: This work merges network connectivity and flow characteristics with enemy threat assessments to identify militarily-useful roads and railways most vulnerable to enemy interdictions. A geographic combatant command recently used this specific research approach to support their request for rapid rail repair capability. © 2019, In accordance with section 105 of the US Copyright Act, this work has been produced by a US government employee and shall be considered a public domain work, as copyright protection is not available.

关键词： Betweenness binary integer programming Graph theory Heuristics Military route vulnerability Shortest path

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Navy operational planner - undersea warfare module

Navy operational planner - undersea warfare module

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作者： Guy A. Molina Naval Postgraduate School

学位级别：硕士

Joint maritime operational planning is the difficult task of assigning various platforms to accomplish a multitude of missions in several areas of operations. The task becomes more difficult as resources are limited, mission requirements evolve, and platform capabilities vary. Emerging threats and technology in the undersea domain have created renewed interest and increased the priority of undersea warfare (USW) planning. This thesis develops and provides a proof-of-concept for a decision-support tool to aid operational planning in a USW environment. Specifically, it provides an optimization model with an optimal solution that maximizes multi-mission achievement in a theater USW environment through the scheduling of surface, sub-surface, and air assets over a non-fixed time horizon. Tactics and their mathematical representation are an input to our model. This makes the model easily adapted to any USW scenario and other warfare areas where mission achievement can be measured quantitatively.

关键词： optimization integer programming binary integer programming navy operational planner maritime operational planning tool decision aid navy logistics navy mission planner NMP NOP USW ASW MIW

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Optimal Design for a Shared Swap Charging System Considering the Electric Vehicle Battery Charging Rate

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ENERGIES 2020年第5期13卷 1213页

作者： Zhong, Lingshu Pei, Mingyang South China Univ Technol Dept Elect Power Guangzhou 510641 Guangdong Peoples R China South China Univ Technol Dept Civil & Transportat Engn Guangzhou 510641 Guangdong Peoples R China Univ S Florida Dept Civil & Environm Engn Tampa FL 33620 USA

Swap charging (SC) technology offers the possibility of swapping the batteries of electric vehicles (EVs), providing a perfect solution for achieving a long-distance freeway trip. Based on SC technology, a shared SC system (SSCS) concept is proposed to overcome the difficulties in optimal swap battery strategies for a large number of EVs with charging requests and to consider the variance in the battery charging rate simultaneously. To realize the optimal SSCS design, a binary integer programming model is developed to balance the tradeoff between the detour travel cost and the total battery recharge cost in the SSCS. The proposed method is verified with a numerical example of the freeway system in Guangdong Province, China, and can obtain an exact solution using off-the-shelf commercial solvers (e.g., Gurobi).

关键词： shared swap charging system electric vehicle operational design battery charging rate binary integer programming

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Bounds on Reliability of Larger Systems by Linear programming with Delayed Column Generation

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JOURNAL OF ENGINEERING MECHANICS 2020年第4期146卷 1-13页

作者： Byun, Ji-Eun Song, Junho Seoul Natl Univ Dept Civil & Environm Engn Seoul 08826 South Korea

In order to accurately assess the reliability of a real-world complex system, the joint distribution of component events is needed. In reality, however, such complete information to model the joint distributions of system components is rarely available. As a way to resort only to the available information while excluding any assumptions on the form of distributions, a linear programming (LP) bounds method was developed in 2003, which computes the narrowest bounds possible for given information regarding marginal and joint failure probabilities. However, the number of variables of the optimization problem exponentially increases as that of component events increases, requiring an insurmountable memory for larger systems. In order to overcome such memory issue, an alternative formulation of the LP bounds method is proposed in this paper. Specifically, an iteration of binary integer programming (BIP) is formulated based on the inclusion relationships between the events of consideration. As a result, the memory requirement can be significantly alleviated with the trade-off of the computational cost required for repeated optimizations of smaller BIP problems. Then, the major bottleneck is changed from the number of component events to that of constraints given as information to narrow the bounds. This paper also provides empirical suggestions on the selection of a subset of constraints to further extend the applicability of the proposed methodology to even larger systems. Five numerical examples of series, parallel, and general system reliability problems are provided to demonstrate the method and its applications.

关键词： Linear programming System reliability bounds Delayed column generation binary integer programming Complex systems Large systems

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Time-preference-based on-spot bundled cloud-service provisioning

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DECISION SUPPORT SYSTEMS 2021年 151卷 113607-113607页

作者： Mukherjee, Anik Sundarraj, Rangaraja P. Dutta, Kaushik Indian Inst Technol Dept Management Studies Roorkee Uttar Pradesh India Indian Inst Technol Dept Management Studies Madras Tamil Nadu India Univ S Florida Muma Coll Business Tampa FL 33620 USA

The cloud computing spot instance is one offering that vendors are leveraging to provide differentiated service to an expanding pay-per-use computing market. Spot instances have cost advantages, albeit at a trade-off of interruptions that can occur when the user's bid price falls below the spot price. The interruptions are often exacerbated since customers often require resources in bundles. For these reasons, customers might have to wait for a long time before their jobs are completed. In this paper, we propose a behavioral-economic model in the form of time-preference-based bids, wherein users are willing to use and bid for services at other times if the vendor cannot provide the resources at the preferred time. Given such bids, we consider the problem of provisioning for such service requests. We develop a time-preference-based optimization model. Since the optimization model is NP-Hard, we develop rule-based genetic algorithms. We have obtained very encouraging results with respect to standard commercial solver as a benchmark. In turn, our results provide evidence for the viability of our approach for online service-provisioning problems.

关键词： Behavioral-economic model Cloud computing Spot Market Time-preference binary integer programming Genetic algorithms

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Incorporating Computation Time Measures During Heterogeneous Features Selection in a Boosted Cascade People Detector

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2016年第8期30卷 1655022-1655022页

作者： Mekonnen, Alhayat Ali Lerasle, Frederic Herbulot, Ariane Briand, Cyril CNRS LAAS 7 Ave Colonel Roche F-31400 Toulouse France Univ Toulouse UPS LAAS F-31400 Toulouse France

In this paper, we investigate the notion of incorporating feature computation time (CT) measures during feature selection in a boosted cascade people detector utilizing heterogeneous pool of features. We present various approaches based on pareto-front analysis, CT weighted adaboost, and binary integer programming (BIP) with comparative evaluations. The novel feature selection method proposed based on BIP - the main contribution - mines heterogeneous features taking both detection performance and CT explicitly into consideration. The results demonstrate that the detector using this feature selection scheme exhibits low miss rates (MRs) with significant boost in frame rate. For example, it achieves a 2.6% less MR at 10(-4) FPPW compared to Dalal and Triggs HOG detector with a 9.22x speed improvement. The presented extensive experimental results clearly highlight the improvements the proposed framework brings to the table.

关键词： People detection feature selection binary integer programming AdaBoost

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Optimal Camera Planning Under Versatile User Constraints in Multi-Camera Image Processing Systems

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2014年第1期23卷 171-184页

作者： Liu, Junbin Sridharan, Sridha Fookes, Clinton Wark, Tim Queensland Univ Technol Image & Video Res Lab Brisbane Qld 4001 Australia

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

关键词： binary integer programming camera placement camera planning multi-camera networks optimization methods reversible jump Markov chain Monte Carlo sensor planning trans-dimensional simulate annealing

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