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linear programming Formulations for Computing Graph Layout Parameters

COMPUTER JOURNAL 2015年第11期58卷 2921-2927页

作者： Gurski, Frank Univ Dusseldorf Inst Comp Sci Algorithm Hard Problems Grp D-40225 Dusseldorf Germany

Luttamguzi et al. [(2005) Integer programming Methods for Several Optimization Problems in Graph Theory. Proc. Int. Conf. Computers and Their Applications, CATA 2005, New Orleans, LA, USA, March 16-18, pp. 50-55. ISCA] have introduced a useful framework for the formulation of graph layout parameters measuring number of edges, which is applied to give linear programming formulations for computing the cut-width, minimum linear arrangement and band-width of a graph. We extend the framework of Luttamguzi et al. by the efficient formulation of sets of vertices of the same neighborhood-so-called groups-using binary linear programming (BIP) conditions. We apply our methods in order to find first BIP formulations for computing the important graph layout para-me-ters path-width, neighborhood-width, linear NLC-width, and linear clique-width. Our formulations give useful and new characterizations of the problems as well as easy-to-understand algorithms for their solution. The size of our formulations is polynomial in the size of the input graph.

关键词： graph algorithms binary linear programming graph parameters graph layout problems

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A maximum expected covering problem for locating and dispatching two classes of military medical evacuation air assets

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OPTIMIZATION LETTERS 2015年第8期9卷 1511-1531页

作者： Grannan, Benjamin C. Bastian, Nathaniel D. McLay, Laura A. Virginia Mil Inst Dept Econ & Business Lexington VA 24450 USA Penn State Univ Dept Ind & Mfg Engn State Coll PA 16802 USA Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA

Military medical evacuation (MEDEVAC) systems respond to casualty incidents and transport the most urgent casualties to a medical treatment facility via multiple types of air ambulance assets. Military MEDEVAC systems are subject to an uncertain number of service calls and each service call demands different system operations depending on type and the priority level. Therefore, military medical planners need an air MEDEVAC asset management system that determines how to dispatch multiple types of air assets to prioritized service calls to maintain a high likelihood of survival of the most urgent casualties. To reach this goal, we propose a novel binary linear programming (BLP) model to optimally locate two types of air assets and construct response districts using a dispatch preference list. Additionally, the BLP model balances the workload among assets and enforces contiguity in the first assigned locations for each air asset. The objective of the BLP model is to maximize the proportion of high-priority casualties responded to within a pre-specified time threshold while meeting performance benchmarks to other types of casualties. A spatial queuing approximation model is derived to provide inputs to the BLP model, which thus reflects the underlying queuing dynamics of the system. We illustrate the model and algorithms with a computational example that reflects realistic military data.

关键词： Air MEDEVAC asset management Casualty triage Spatial queuing binary linear programming Military medicine

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Optimization in dubbing scheduling

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TOP 2015年第3期23卷 685-702页

作者： Brisaboa, Nieves R. Carpente, Luisa Cerdeira-Pena, Ana Lorenzo-Freire, Silvia Univ A Coruna Fac Comp Sci Dept Comp Sci Database Lab La Coruna 15071 Spain Univ A Coruna Fac Comp Sci Dept Math MODES Res Grp La Coruna 15071 Spain

One of the main tasks in dubbing studios is to design good schedules to assign actors/actresses to dubbing sessions. This paper provides an effective tool based on the simulated annealing philosophy. The performance of the proposed heuristic is guaranteed by a binary linear programming model (BP model). By relaxing some integrality conditions in the BP model, we can achieve optimal schedules in real instances gathered from several dubbed films. Yet, in most cases, it is not possible to obtain these optimal schedules in a suitable computational time. On the contrary, the heuristic algorithm gets high quality solutions (and even the optimal ones) in just few seconds.

关键词： Dubbing Scheduling Simulated annealing binary linear programming

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A New Method on Inshore Ship Detection in High-Resolution Satellite Images Using Shape and Context Information

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2014年第3期11卷 617-621页

作者： Liu, Ge Zhang, Yasen Zheng, Xinwei Sun, Xian Fu, Kun Wang, Hongqi Chinese Acad Sci Inst Elect Key Lab Technol Geospatial Informat Proc & Applic Beijing 100190 Peoples R China

In this letter, we present a new method to detect inshore ships using shape and context information. We first propose a new energy function based on an active contour model to segment water and land and minimize it with an iterative global optimization method. The proposed energy performs well on the different intensity distributions between water and land and produces a result that can be well used in shape and context analyses. In the segmented image, ships are detected with successive shape analysis, including shape analysis in the localization of ship head and region growing in computing the width and length of ship. Finally, to locate ships accurately and remove the false alarms, we unify them with a binary linear programming problem by utilizing the context information. Experiments on QuickBird images show the robustness and precision of our method.

关键词： Active contour model binary linear programming context information inshore ship detection shape analysis

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DCA based algorithms for multiple sequence alignment (MSA)

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CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH 2014年第3期22卷 501-524页

作者： Hoai An Le Thi Tao Pham Dinh Belghiti, Moulay Univ Lorraine Lab Theoret & Appl Comp Sci UFR MIM F-57045 Metz France Natl Inst Appl Sci Rouen Math Lab F-76801 St Etienne France

In the last years many techniques in bioinformatics have been developed for the central and complex problem of optimally aligning biological sequences. In this paper we propose a new optimization approach based on DC (Difference of Convex functions) programming and DC Algorithm (DCA) for the multiple sequence alignment in its equivalent binary linear program, called "Maximum Weight Trace" problem. This problem is beforehand recast as a polyhedral DC program with the help of exact penalty techniques in DC programming. Our customized DCA, requiring solution of a few linear programs, is original because it converges after finitely many iterations to a binary solution while it works in a continuous domain. To scale-up large-scale (MSA), a constraint generation technique is introduced in DCA. Preliminary computational experiments on benchmark data show the efficiency of the proposed algorithm DCAMSA, which generally outperforms some standard algorithms.

关键词： Multiple sequence alignment Maximum weight trace Exact penalty binary linear programming DC programming DCA Constraint generation

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Integration of Renewable Energy in Demand-Side Management for Home Appliances 2

Integration of Renewable Energy in Demand-Side Management fo...

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International Renewable and Sustainable Energy Conference (IRSEC)

作者： Jaradat, Manar Jarrah, Moath Jararweh, Yaser Al-Ayyoub, Mahmoud Bousselham, Abdelkader Jordan Univ Sci & Technol Irbid Jordan Environm & Energy Res Inst Doha Qatar

ISBN: (纸本)9781479973361

Environmental concerns and high prices of fossil fuels increase the feasibility of using renewable energy sources in smart grid. Nowadays many homes adopt the use of renewable energy sources to satisfy their load demand. In this paper we propose a mechanism for scheduling load demand of home appliances according to the availability of renewable energy and varying price of grid energy. binary linear programming is used to model the proposed mechanism. Two types of appliances are used in this model: 1) Must run appliances. 2) Scheduled appliances. The proposed mechanism aims to minimize smart home electricity cost by maximizing the usage of renewable energy. Simulation shows that the proposed energy scheduling mechanism minimizes total electricity cost by 48% and maximizes the used renewable energy to be 65% of the total generated renewable energy.

关键词： Demand-side management load scheduling renewable energy binary linear programming

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Charging Strategies to Minimize the Energy Cost for an Electric Vehicle Fleet

Charging Strategies to Minimize the Energy Cost for an Elect...

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5th IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Van-Linh Nguyen Tuan Tran-Quoc Bacha, Seddik Ngoc-An Luu Univ Grenoble Alpes G2Elab F-38000 Grenoble France CEA INES Paris France Univ Grenoble Alpes CEA INES F-73377 Le Bourget Du Lac France

ISBN: (纸本)9781479977208

In the paper, we consider the charging scheduling of the electric vehicles (EVs) at a charging station with multiple charge points. The charging station is equipped with photovoltaic (PV) generator and can buy or sell energy to power grid. The paper proposes charging strategies to reduce the charging cost of the charging station under time-varying electricity price signals. These strategies are based on the interruption (on/off) or on the modulation of EV charging power. By dividing the daytime in many intervals, a binary linear programming and a linear programming is used, respectively for each strategy, to manage the charging plan of the vehicles. The first application is used for reducing total energy cost in daytime. The second application is proposed to limit the charging power and reducing total energy cost simultaneously during a time defined by DSO (or another operator). The proposed method takes into account the random time arrival and random time departure of vehicle. The performance of the proposed strategies is validated by simulations for a charging station of 50 electric vehicles in real time conditions.

关键词： binary linear programming EV charging management electric vehicle energy cost photovoltaic

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Charging Strategies to Minimize the Peak Load for an Electric Vehicle Fleet

Charging Strategies to Minimize the Peak Load for an Electri...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Van-Linh NGUYEN Tuan TRAN-QUOC Seddik BACHA Be NGUYEN Univ. Grenoble Alpes G2Elab Univ. Grenoble Alpes CEA/INES Da Nang Vocational Training College

ISBN: (纸本)9781479940318

Charging of a large number of electric vehicles (EV) at the same time raises several technical problems or can have significant impacts on power systems like high peak power consumption. During daytime, when EVs are connected at the different charging stations at the same time, they can cause a congestion problem in the network. The paper proposes charging strategies to reduce the peak load. These strategies are based on the interruption (on/off) or the modulation of EV charging power. By dividing the daytime in many intervals, a binary linear programming combined with the bisection scheme is used to manage the charging plan of the vehicles. The first application is used for reducing peak load in daytime. The second application is proposed to limit the charging power during a time defined by DSO (or TSO). The performance of the proposed strategies is validated by simulations for a charging station of 50 electric vehicles with a fast calculation time. The results obtained show that peak power can be reduced by more than 50 per cent.

关键词： binary linear programming Charging management Charging station Electric vehicle Peak shaving

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Deriving a minimum distance-based collective preorder: a binary mathematical programming approach

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OR SPECTRUM 2012年第1期34卷 23-42页

作者： Jabeur, Khaled Martel, Jean-Marc Guitouni, Adel ISCCB Zarzouna 7021 Bizerte Tunisia Univ Laval Fac Sci Adm Ste Foy PQ G1K 7P4 Canada Def R&D Canada Valcartier Val Belair PQ G3J 1X5 Canada

Deriving the "closest" (minimal distance) collective judgment to all individual opinions is a complex aggregation problem that has been widely studied in group decision-making literature. However, most of the existing literature does not consider individual opinions expressed as partial preorders (i.e., a preference system which includes the incomparability relation). In this paper, we propose a method based on binary linear programming to derive a minimum distance-based collective preorder from individual preferences relational systems (p.r.s.). This method is threefold. First, each member determines a preorder (partial or total) over the set of alternatives. Second, an aggregation algorithm is proposed to derive at least one collective and not necessary transitive p.r.s. at minimum distance from all individual preorders. Third, a binary linear programming optimization will transform each non-transitive collective p.r.s. into a collective preorder (i.e. a transitive p.r.s.). The proposed method has three main advantages: (1) it deals with incomparability (partial preorders), (2) the relative importance of the members is explicitly considered and (3) the collective p.r.s. obtained after the aggregation step might be "exploited" according to different decision-making problematics (i.e. ranking, choice and sorting).

关键词： Group decision-making binary relations Preferences aggregation Distance measure binary linear programming Members' relative importance

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Exploiting transmission opportunities in heterogeneous wireless networks: a transmission power saving perspective

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SCIENCE CHINA Information Sciences 2013年第2期57卷 022313-022313页

作者： JU HongHao LI JianDong LONG Yan YANG XiaoNiu State Key Laboratory of Integrated Service Networks Xidian University Xi'an 710071 China No36 Research Institute of China Electronics Technology Group Corporation Jiaxing 314033 China

Exploiting transmission opportunities in dimensions of user equipments (UEs), radio access networks (RANs), and radio resource units (RRUs), in heterogeneous wireless networks (HWNs), we focus on a new perspective of saving the uplink transmission power, so as to lengthen the battery life time of UEs. Moreover, to ensure the quality of service for each UE, we guarantee each a minimal transmission rate. To achieve the above HWN control objective, we have to make an efficient matching among UEs, RANs, and RRUs, which is formulated as a binary linear optimization problem. Due to its NP-hard complexity, we develop a rate-power efficiency based HWN control algorithm with low computational complexity. We verify the performance of our HWN control scheme through simulation. Extensive simulation results demonstrate the advantage of our HWN control method in saving the uplink transmission power and guaranteeing the UE transmission rate requirement.

关键词： heterogeneous wireless networks power saving minimal rate requirement binary linear programming rate-power efficiency

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