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A note on the Clustered Set Covering Problem

DISCRETE APPLIED MATHEMATICS 2014年第Part1期164卷 13-19页

作者： Alfandari, Laurent Monnot, Jerome ESSEC Business Sch F-95021 Cergy Pontoise France CNRS UMR 7243 F-75775 Paris France Univ Paris 09 LAMSADE F-75775 Paris France

We define an NP-hard clustered variant of the Set Covering Problem where subsets are partitioned into K clusters and a fixed cost is paid for selecting at least one subset in a given cluster. We show that the problem is approximable within ratio (1+epsilon)(e/e-1)H(q), where q is the maximum number of elements covered by a cluster and H(q) = Sigma(q)(l=1) 1/l (C) 2011 Elsevier E.V. All rights reserved.

关键词： Integer programming Set covering maximal coverage Approximation

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Optimization and Deployment of Survivable Fiber-Wireless (FiWi) Access Networks with Integrated Small Cell and WiFi

Optimization and Deployment of Survivable Fiber-Wireless (Fi...

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IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB)

作者： Yu, Yinpeng Ranaweera, Chathurika Lim, Christina Wong, Elaine Guo, Lei Liu, Yejun Nirmalathas, Ampalavanapillai Univ Melbourne Dept Elect & Elect Engn Melbourne Vic 3010 Australia Univ Melbourne Melbourne Networked Soc Inst Melbourne Vic 3010 Australia Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China

ISBN: (纸本)9781467365550

Fiber-Wireless (FiWi) access network as a small cell backhaul is now becoming a promising architecture to satisfy the rapid growth of demand for mobile data traffic. With increasing amount of network traffic, the failure of network components such as distribution fiber link failure may lead to unpredictable service outages. The network survivability through protection and restoration has become a critical requirement. Thus, in this paper, we explore the protection mechanism for small cells by integrating WiFi and rerouting of data traffic over WiFi to offer some restoration of backhaul capacity. Using this architecture, we propose a novel method to optimize the deployment and maximize the coverage of survivable FiWi access network, with appropriate constraints from connectivity, survivability, capacity and delay perspectives. Our simulation results show the successful reconfiguration of survivable FiWi access networks with integrated small cell and WiFi under different simulated network failure scenarios and we demonstrate feasibility of the proposed optimization method.

关键词： Fiber-Wireless (FiWi) Access Networks network survivability small cell maximal coverage

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Placement of ONUs and Wireless Routers in Fiber-Wireless Access Network with Survivability Constraints

Placement of ONUs and Wireless Routers in Fiber-Wireless Acc...

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2nd International Conference on Information Technology and Management Innovation (ICITMI 2013)

作者： Yu, Yinpeng Liu, Yejun Peng, Yuhuai Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China

ISBN: (纸本)9783037858646

Survivability is one of the key issues in Fiber-Wireless (FiWi) access network since a single network component failure may cause enormous data loss. This paper focuses on survivability of citywide FiWi access network and proposes a scheme using Integer Linear Programming (ILP) to tolerate the failures of distribution fiber and WiFi routers considering coverage problem. Simulation shows good performance of this scheme. When WiFi routers and ONUs are places in suitable potential sites, the maximal coverage of uses and survivability of FiWi access network are realized.

关键词： maximal coverage survivability FiWi network Integer Linear Programming (ILP)

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Maximizing Wireless Mesh Network coverage

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INTERNATIONAL REGIONAL SCIENCE REVIEW 2011年第4期34卷 419-437页

作者： Shillington, Luke Tong, Daoqin Univ Arizona Sch Geog & Dev Tucson AZ 85721 USA

As an emerging technology, wireless communication revolutionizes the way data are shared and transferred. In particular, wireless mesh network (WMN) technology allows data transmission from one node to another without extensive cabling. In this article, spatial characteristics of maximal covering problems are explored, and a novel spatial optimization model is proposed for WMN topology planning. The model selects the optimal locations for network infrastructure to achieve the maximal coverage of spatial demand. Additionally, important WMN design requirements have been accounted for, including network topology and throughput capacity. The validity of the model is tested through a WMN deployment developed for an emergency medical service application in Tucson, Arizona.

关键词： wireless mesh network network topology planning maximal coverage spatial optimization

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Approximation of the clustered set covering problem

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Electronic Notes in Discrete Mathematics 2010年第C期36卷 479-485页

作者： Alfandari, Laurent Monnot, Jérôme ESSEC Business School BP105 95021 Cergy Pontoise Av. Bernard Hirsch France CNRS FRE 3234 F-75775 Paris France Université Paris-Dauphine LAMSADE F-75775 France

We define a NP-hard clustered variant of the Set Covering Problem where subsets are partitioned into K clusters and a fixed cost is paid for selecting at least one subset in a given cluster. This variant can reformulate as a master problem various multi-commodity flow problems in transportation planning. We show that the problem is approximable within ratio (1+∈)(e/e-1)H(q), where q is the maximum number of elements covered by a cluster and H(q)=∑_i=1 ^q 1/i. © 2010 Elsevier B.V.

关键词： Approximation Integer Programming maximal coverage NP-hardness Set Covering

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Heuristics in Spatial Analysis: A Genetic Algorithm for coverage Maximization

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ANNALS OF THE ASSOCIATION OF AMERICAN GEOGRAPHERS 2009年第4期99卷 698-711页

作者： Tong, Daoqin Murray, Alan Xiao, Ningchuan Univ Arizona Sch Geog & Dev Tucson AZ 85721 USA Arizona State Univ Sch Geog Sci Tempe AZ 85287 USA Ohio State Univ Dept Geog Columbus OH 43210 USA

Many government agencies and corporations face locational decisions, such as where to locate fire stations, postal facilities, nature reserves, computer centers, bank branches, and so on. To reach such location-related decisions, geographical information systems (GIS) are essential for providing access to spatial data and analysis tools. Moreover, geographic insights can be gained from GIS as they enable capabilities for better reflecting problems of interest in location modeling. The resulting models can be complex, however, and hence computationally challenging to solve. This article examines an important model for regional service coverage maximization. This model is solved heuristically using a genetic algorithm. The new heuristic innovatively incorporates problem-specific knowledge by exploring the geographical structure of the problem under study. Comparative application results demonstrate important nuances of the new genetic algorithm, enhancing overall performance.

关键词： facility location genetic algorithm heuristics maximal coverage spatial analysis

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Distributed Energy Resources and Fast Charging Stations Allocation for Enhanced System Operation and Charging Infrastructure coverage 15

Distributed Energy Resources and Fast Charging Stations Allo...

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15th Seminar on Power Electronics and Control (SEPOC)

作者： Ferraz, Rafael S. F. Ferraz, Renato S. F. Junior, Vanio F. S. Rueda-Medina, Augusto C. Fardin, Jussara F. Univ Fed Espirito Santo PPGEE Postgrad Program Elect Engn Vitoria ES Brazil

ISBN: (纸本)9798350312898

The growing insertion of Electric Vehicles (EVs) in the distribution system is a promising solution to mitigate the greenhouse emission issue. However, as the number of EVs significantly increases, the excessive charging demand of Fast Charging Stations (FCSs) may lead to instability problems in the distribution network. Therefore, this paper proposes a multi-objective optimization approach for the allocation and sizing of Fast Charging Stations (FCSs) with the objective of minimizing their installation and operation costs, while maximizing the coverage for EVs. It is well-known that the integration of EVs results in increased power losses. As a consequence, in this study, an optimized planning of Distributed Energy Resources (DERs) was also performed with the purpose of mitigating this issue. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) was applied to obtain the Pareto curve, which made it possible to minimize the objective functions for the 33-bus test feeder and 25-node transportation network, considering commercial and residential areas. Based on the solution selected by the Fuzzy Decision-Making method, it was possible to minimize the voltage deviation even with the insertion of the FCSs in the system.

关键词： Distributed Energy Resource Fast Charging Station maximal coverage Non-dominated Sorting Genetic Algorithm II Power Quality Indices

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Investigating Surrogate Point-based Modeling Approach for Covering Continuous Spatial Demand 18

Investigating Surrogate Point-based Modeling Approach for Co...

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18th IEEE International Conference on Intelligent Transportation Systems

作者： Hsieh, Pei-Shan Lin, Wei-Hua Qi, Mingyao Tong, Daoqin Univ Arizona Dept Syst & Ind Engn Tucson AZ 85721 USA Tsinghua Univ Grad Sch Shenzhen Modern Logist Res Ctr Shenzhen 518057 Peoples R China Univ Arizona Sch Geog & Dev Tucson AZ 85721 USA

ISBN: (纸本)9781467365963

The facility location problem (FLP) has broad applications in transportation, ranging from siting electric vehicle charging stations to positioning emergency vehicles. The spatial facility location problem (SFLP) considers continuous demand of a region where facilities can be placed anywhere. One of the approaches to solving the SFLP is to aggregate the demand into discrete points first and then solve the corresponding pointbased FLP as a surrogate model. The model performance, however, is measured by the percentage of the continuous space actually covered. The solution to the classic FLP is often not unique. In this paper, we explore how the behavior of the solution to the FLP would affect the quality of the coverage to the spatial demand. We examine in detail the property of the surrogate model and identify the key contributing factor that would affect the quality of the solution to the original coverage problem for covering continuous spatial demand. Our goal is to find a surrogate model that is detailed enough to capture all the key elements of the problem and achieve the desired accuracy level, yet has the size that can be handled by the existing computing power.

关键词： Continuous space maximal coverage facility location

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coverage Location Models: Alternatives, Approximation, and Uncertainty

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INTERNATIONAL REGIONAL SCIENCE REVIEW 2016年第1期39卷 48-76页

作者： Wei, Ran Univ Utah Dept Geog Salt Lake City UT 84112 USA

Achieving maximal coverage of service facilities has been of great interest to urban and regional planners. Examples include placing cellular towers, siting emergency response stations, and locating weather radars, among others. In some planning contexts, facilities could be sited almost anywhere in a region due to their small geographic footprints and demand is continuously distributed. This location problem has been represented as the continuous space maximal coverage problem (CSMCP). The CSMCP is widely acknowledged to be challenging to solve exactly. A broadly used solution approach for the CSMCP is to transform the problem into discrete maximal coverage models through continuous space discretization. A variety of discrete simplifications of CSMCP have been developed, attempting to address spatial representation issues that arise in the application of discrete models used as a continuous space approximation. However, the performance of applying these discrete coverage models to approximately solving the CSMCP has not been explicitly evaluated. It remains elusive as to which approach provides the best approximation for the CSMCP. This article therefore presents a comparative performance analysis of various discrete approximations for the CSMCP. Empirical results provide insights on how to achieve a balance between model representation detail and reasonable computation. Potential research directions are also suggested.

关键词： maximal coverage continuous space discretization

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A note on the Clustered Set Covering Problem

A note on the Clustered Set Covering Problem

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1st International Symposium on Combinatorial Optimization (ISCO)

作者： Alfandari, Laurent Monnot, Jerome ESSEC Business Sch F-95021 Cergy Pontoise France CNRS UMR 7243 F-75775 Paris France Univ Paris 09 LAMSADE F-75775 Paris France

关键词： Integer programming Set covering maximal coverage Approximation

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