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13th IEEE and IFIP International Conference on Wireless and Optical Communications Networks (WOCN)

作者： Choudhary, Raman Kumar, Sujeet Deepak, Akshay Dash, Dinesh Natl Inst Technol Dept Comp Sci & Engn Patna 800005 Bihar India

ISBN: (纸本)9781467389754

Wireless Sensor Network is huge number of sensor nodes disposed randomly in severe field to gather data. It monitors physical phenominan changes such as temperature, pressure, humidity, solar radition, ambident light extra. Sensor nodes are small in size, having less energy, less communication power, less cost and multi functional nodes. This paper we firstly discuss about different types types of network, protocols extra i. e Network such as Direct network, hierarchical network etc and protocols like LEACH, PEGASIS. Next in this paper we deployed sensor nodes randomly in the grid network, We focus on data aggregation in different type of sitution known as critical zone, in critical zone(critical grid) senor nodes are heavly loaded with information. Our objective is to maximize the data generation rate of sensor nodes. To got this objective we form different integer linear programming formulation. A optimization tool such as CPLEX IBM ILOG used for optimization and to show critical grids aggregation used MATLAB.

关键词： Sensor Network integer linear programming Energy Model Critical grids Normal grids

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An integer linear programming approach to maintenance strategies selection

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INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT 2013年第9期30卷 991-+页

作者： Braglia, Marcello Castellano, Davide Frosolini, Marco Univ Pisa Pisa Italy ANIMP Natl Assoc Ind Plants Milan Italy Univ Pisa Ind Plant Pisa Italy

Purpose - The purpose of this paper is to present a reliability centered maintenance (RCM) embedded integer linear programming approach (suited to the budget monetary resources allocation task) to the maintenance strategies mix selection for an industrial plant equipment. Design/methodology/approach - The developed approach allows to determine the optimal maintenance strategies mix for a set of equipment in a more quantitative way than the classic RCM approach. The proposed model takes into account, for each potential failure determined using the FMECA and for each admissible strategy, the costs and the potential risk priority number (RPN) reduction. Finally, an industrial case concerning an Italian paper-mill plant is reported to demonstrate the effectiveness of the approach presented. Findings - The paper finds that the application of the proposed approach allows to optimally allocate the budget monetary resources, determining which suitable maintenance practice apply to each failure, taking into account the costs of each strategy and the potential reduction of the RPN. Practical implications - The proposed model permits to assign (during the budget monetary resources allocation task) to each failure the optimal strategy, among a set of suitable maintenance practices, considering the costs and the estimated RPN reduction. Originality/value - The paper proposes a completely new RCM embedded approach to the maintenance strategies selection, in order to optimally allocate the budget monetary resources. This model overcomes the limits of the traditional RCM approach, taking into account quantitative aspects, i.e. the compatibility constraint between failures and policies, the maintenance strategies costs, and the RPN estimated reduction.

关键词： FMECA integer linear programming Reliability centered maintenance

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An integer linear programming Approach for the Combined Cell Layout Problem

An Integer Linear Programming Approach for the Combined Cell...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM)

作者： Anjos, Miguel F. Hungerlaender, Philipp Maier, Kerstin GERAD Montreal PQ H3C 3A7 Canada Polytech Montreal Montreal PQ H3C 3A7 Canada Alpen Adria Univ Klagenfurt Dept Math A-9020 Klagenfurt Austria

ISBN: (纸本)9781538667866

The Combined Cell Layout Problem aims to minimize the material handling costs in a cellular manufacturing system with at least two cells where processing occurs, and in the presence of pieces that need to be processed in more than one cell. The alignment of the machines in each cell can follow a row or a circular layout. We propose an integer linear programming approach for solving this problem. In a computational study we show that our approach is able to solve instances with up to 240 machines arranged in 10 cells to optimality within one minute.

关键词： Facility planning and design circular layout single-row layout combined cell layout integer linear programming

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CELL TRACKING BASED ON integer linear programming AND PROBABILITY SCORES 21

CELL TRACKING BASED ON INTEGER LINEAR PROGRAMMING AND PROBAB...

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21st IEEE International Symposium on Biomedical Imaging (ISBI)

作者： Lux, Filip Matula, Petr Masaryk Univ Fac Informat Bot 68a Brno 60200 Czech Republic

ISBN: (纸本)9798350313345;9798350313338

The cell tracking problem can be formulated as a global optimization problem based on integer linear (IL) programming. The obtained solution depends on the definition of the IL program and the chosen costs of the events considered in the problem formulation. In general, balancing meaningful costs across different events is difficult. To simplify this problem, we propose a cost assignment approach based on probability scores, allowing us to easily interpret the free parameters. The idea is presented based on the BF-C2DL-HSC dataset from the Cell Tracking Challenge. We show our method reaches state-of-the-art performance when evaluating both technical and biological tracking measures.

关键词： Cell Tracking Tracking-by-Assignment integer linear programming Cost Assignment

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Using integer linear programming for correctly rounded multipartite architectures 21

Using integer linear programming for correctly rounded multi...

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21st International Conference on Field-Programmable Technology (ICFPT)

作者： Desrentes, Oregane de Dinechin, Florent Ecole Normale Super Lyon Lyon France Univ Lyon INSA Lyon INRIA CITI Lyon France

ISBN: (数字)9781665453363

ISBN: (纸本)9781665453363

This article introduces several improvements to the multipartite method, a generic technique for the hardware implementation of numerical functions. A multipartite architecture replaces a table of value with several tables and an adder tree. Here, the optimization of multipartite tables is formalized using integer linear programming so that generic ILP solvers can be used. This improves the quality of faithfully rounded architectures compared to the state of the art. The proposed approach also enables correctly rounded multipartite architectures, providing errorless table compression. This improves the area by a factor 5 without any performance penalty compared with the state of the art in errorless compression. Another improvement of the proposed work is a cost function that attempts to predict the total cost of an architecture in FPGA architectural LUTs, where most of the previous works only count the size of the tables, thus ignoring the cost of the adder tree.

关键词： Costs integer linear programming linear programming Cost function Hardware Table lookup Field programmable gate arrays

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New Support Size Bounds and Proximity Bounds for integer linear programming 49th

New Support Size Bounds and Proximity Bounds for Integer Lin...

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49th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM)

作者： Berndt, Sebastian Mnich, Matthias Stamm, Tobias Univ Lubeck Inst Theoret Comp Sci Lubeck Germany Hamburg Univ Technol Inst Algorithms & Complex Hamburg Germany

ISBN: (纸本)9783031521126;9783031521133

integer linear programming (ILP) is a fundamental research paradigm in algorithms. Many modern algorithms to solve structured ILPs efficiently follow one of two main approaches. The first one is to prove a small upper bound on the support size of the ILP, which is the number of variables taking non-zero values in an optimal solution, and then to only search for ILP solutions of small support. The second one is to apply an augmentation algorithm using Graver elements to an initial feasible solution obtained from a small proximity bound for the ILP, which is the distance between an optimal solution of the ILP and that of its LP relaxation. Our first contribution are new lower bounds for the support size of ILPs. Namely, we discover a connection between support sizes and an old number-theoretic conjecture by Erdos on subset-sum distinct sets. Further, we improve the previously best lower bounds on the support size of ILPs with m constraints and largest absolute value Delta of any coefficient in the constraint matrix from Omega(mlog(Delta)) to Omega(mlog(root m Delta)). This new lower bound asymptotically matches the best-known upper bounds. Our second contribution are new bounds on the size of Graver elements and on the proximity for ILPs. We first show nearly tight lower and upper bounds for g(1)(A), the largest 1-norm parallel to g parallel to(1) of any Graver basis element g of the constraint matrix A. Then we show that the proximity of any ILP in standard form with support size s is bounded by s center dot c(1)(A), where c(1)(A) is the largest 1-norm parallel to c parallel to(1) of any circuit c of A. This improves over the known proximity bound of n center dot g(1)(A), as s and c(1)(A) can be much smaller than n and g(1)(A), respectively.

关键词： integer linear programming proximity bounds Graver bases

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On the foundations of linear and integer linear programming I

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Mathematical programming 1975年第1期9卷 207-226页

作者： Graver, Jack E. Syracuse University Syracuse New York United States

In this paper we consider the question: how does the flow algorithm and the simplex algorithm work? The usual answer has two parts: first a description of the "improvement process", and second a proof that if no further improvement can be made by this process, an optimal vector has been found. This second part is usually based on duality -a technique not available in the case of an arbitrary integer programming problem. We wish to give a general description of "improvement processes" which will include both the simplex and flow algorithms, which will be applicable to arbitrary integer programming problems, and which will in themselves assure convergence to a solution. Geometrically both the simplex algorithm and the flow algorithm may be described as follows. At the ith stage, we have a vertex (or feasible flow) to which is associated a finite set of vectors, namely the set of edges leaving that vertex (or the set of unsaturated paths). The algorithm proceeds by searching among this special set for a vector along which the gain function is increasing. If such a vector is found, the algorithm continues by moving along this vector as far as is possible while still remaining feasible. The search is then repeated at this new feasible point. We give a precise definition for sets of vectors, called test sets, which will include those sets described above arising in the simplex and flow algorithms. We will then prove that any "improvement process" which searches through a test set at each stage converges to an optimal point in a finite number of steps. We also construct specific test sets which are the natural extensions of the test sets employed by the flow algorithm to arbitrary linear and integer linear programming problems. © 1975 The Mathematical programming Society.

关键词： programming Problem integer linear programming Natural Extension linear programming Problem Optimal Point

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A Novel integer linear programming Based Optimal PMU Placement Model

A Novel Integer Linear Programming Based Optimal PMU Placeme...

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North American Power Symposium (NAPS)

作者： Li, Yikui Li, Jie Wu, Lei Clarkson Univ Dept Elect & Comp Engn Potsdam NY 13699 USA

ISBN: (纸本)9781538671382

State estimator is the foundation of system awareness as well as a variety of other widely deployed applications. Indeed, the deployment of phasor measurement units (PMU) has highly advanced the accuracy and granularity of state estimators. However, deploying PMUs to all buses is neither physically necessary nor financially viable for granting full observability of the system. Consequently, by leveraging system observability and capital costs of PMUs, PMUs could be optimally placed in a system that would minimize total investment costs while also satisfying observability requirements. This paper proposes a novel integer linear programming (ILP) based optimal PMU placement (OPP) model, in which detailed PMU installation costs are considered. More importantly, different from existing OPP models that are based on network connectivity matrix, the proposed model defines bus observability indicators to explicitly describe how individual buses achieve their observability, namely propagation of the observability from one bus to another. In addition, contributions of zero injection buses for providing extra observability and consequently reducing total investment cost are accurately formulated via carefully crafted constraints. Numerical studies illustrate effects of the proposed approach.

关键词： Optimal PMU placement integer linear programming Phasor measurement unit Wide area measurement system Zero injection bus

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An integer linear programming model for the constrained shortest path tour problem

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Electronic Notes in Discrete Mathematics 2018年 69卷 141-148页

作者： de Andrade, Rafael Castro Saraiva, Rommel Dias Department of Statistics and Applied Mathematics Federal University of Ceará Campus do Pici BL 910 CEP Fortaleza 60.440-900 Brazil Department of Computer Science Federal University of Ceará Campus do Pici BL 910 CEP Fortaleza 60.455-760 Brazil

Let D = (V, A) be a directed graph with set of vertices V and set of arcs A, and let each arc (i, j) ∈ A, with i, j ∈ V, be associated with a non-negative cost. The constrained shortest path tour problem (CSPTP) is NP-Hard and consists in finding a shortest path between two distinct vertices s ∈ V and t ∈ V such that the path does not include repeated arcs and must visit a sequence of vertex disjoint subsets T₁, …, T_N in this order. In this work, we formulate the CSPTP as an integer linear programming (ILP) model and present valid inequalities for the problem. Computational experiments performed on benchmark data sets from the literature show that our ILP model consistently outperforms existing exact algorithms for the CSPTP and finds optimal solutions for most instances. © 2018 Elsevier B.V.

关键词： Combinatorial optimization Constrained shortest path tour problem integer linear programming Network flow problems

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Scalable Mapping of Streaming Applications onto MPSoCs using Optimistic Mixed integer linear programming 26

Scalable Mapping of Streaming Applications onto MPSoCs using...

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26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP)

作者： Gayen, Neela Kelly, Wayne Tang, Maolin Ax, Johannes Flasskamp, Martin Klarhorst, Christian Jungeblut, Thorsten Queensland Univ Technol Fac Sci & Engn Brisbane Qld Australia Bielefeld Univ CITEC Cognitron & Sensor Syst Grp Bielefeld Germany

ISBN: (纸本)9781538649756

Embedded streaming applications are facing increasingly demanding performance requirements in terms of throughput. A common mechanism for providing high compute power with a low energy budget is to use a very large number of low-power cores, often in the form of a Massively Parallel System on Chip (MPSoC). The challenge with programming such massively parallel systems is deciding how to optimally map the computation to individual cores for maximizing throughput. In this work we present an automatic parallelizing compiler for the StreamIt programming language that efficiently and effectively maps computation to individual cores. The compiler must be both effective, meaning that it does a good job of optimizing for throughput;but also efficient, in that the time taken to find such a mapping must scale well as the number of cores and size of the Stream program increases. We improve on previous work that used integer linear programming (ILP) to map StreamIT programs to multicore systems by formulating the mapping problem in a different way using mostly real rather than integer variables. Using so called Mixed integer linear programming (MILP) dramatically reduces the cost compared to standard ILP. This alternative formulation creates what we call an optimistic solution that we then need to adjust slightly to obtain a final feasible solution. We show that this new approach is always close, if not better in terms of effectiveness, while being dramatically better in terms of scalability and efficiency.

关键词： streamIt integer linear programming scalable mapping

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