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A Bi-objective integer linear programming model for the routing and network coding assignment problem in WDM optical networks with dedicated protection

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COMPUTER COMMUNICATIONS 2019年 133卷 51-58页

作者： Dao Thanh Hai Vietnam Natl Univ Int Sch Lab Data Sci & Optimizat Complex Syst Hanoi Vietnam

The explosive traffic growths are pushing the transport network close to its capacity limitation, raising critical issues about fiber capacity crunch. In this context, network coding has been emerging as the promising technique to improve the network capacity efficiency thanks to the capability of better resources utilization. The application of network coding to the realms of failure recovery in optical networks has paved the new way for more efficient protection schemes and indeed, XOR network coding combined with dedicated protection has been proposed, investigated and developed to challenge the well-established understanding of trading capacity efficiency for recovery speed and vice versa. In order to maximize the benefits empowered by network coding in this case, the problem of 1 + 1 routing and network coding assignment (1 + 1 RNCA) has to be optimally solved. Apart from traditional 1 + 1 routing, the decision of network coding information has also to be taken into account including the selection of pair of demands for encoding and the respective coding node and coding links. In this paper, we propose a bi-objective integer linear programming model of the 1 + 1 RNCA problem aiming at minimizing the conventional routing cost as the primary objective and furthermore minimizing the number of nodes with coding capabilities as the secondary objective. Our formulation uses a weighting method to combine two objectives into an integrated one and we provide a rigorous analysis on configuring the weight coefficients to capture the desired priority of individual objectives. The efficiency of our integrated objective model in comparison with reference designs based on the single-objective model, 1 + 1 routing and 1 + 1 RNCA, is numerically evaluated on different realistic topologies and traffic sets. Extensive simulation demonstrates that our proposal outperforms traditional approaches when it could achieve the lowest routing cost while simultaneously employing minimal nu

关键词： Routing Dedicated protection WDM optical networks Network coding integer linear programming Bi-objective model

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Learning Bayesian network structure: Towards the essential graph by integer linear programming tools

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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 2014年第4期55卷 1043-1071页

作者： Studeny, Milan Haws, David Inst Informat Theory & Automat ASCR Prague Czech Republic IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA

The basic idea of the geometric approach to learning a Bayesian network (BN) structure is to represent every BN structure by a certain vector. If the vector representative is chosen properly, it allows one to re-formulate the task of finding the global maximum of a score over BN structures as an integer linear programming (ILP) problem. Such a suitable zero-one vector representative is the characteristic imset, introduced by Student, Hemmecke and Lindner in 2010, in the proceedings of the 5th PGM workshop. In this paper, extensions of characteristic imsets are considered which additionally encode chain graphs without flags equivalent to acyclic directed graphs. The main contribution is a polyhedral description of the respective domain of the ILP problem, that is, by means of a set of linear inequalities. This theoretical result opens the way to the application of ILP software packages. The advantage of our approach is that, as a by-product of the ILP optimization procedure, one may get the essential graph, which is a traditional graphical BN representative. We also describe some computational experiments based on this idea. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Learning Bayesian network structure integer linear programming Characteristic imset Essential graph

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Using integer linear programming to minimize the embodied CO2 emissions of the opaque part of a facade

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BUILDING AND ENVIRONMENT 2020年 177卷

作者： Soler, David Salandin, Andrea Bevivino, Michele Univ Politecn Valencia Inst Univ Matemat Multidisciplinar Cami Vera S-N Valencia 46022 Spain Univ Politecn Valencia Ctr Tecnol Fis Cami Vera S-N Valencia 46022 Spain Via Fiume 6 I-39100 Bolzano Italy

Buildings are responsible for about 36% of the CO2 emissions in Europe but there is a significant potential to reduce these emissions. This paper deals with the embodied CO2 emissions of the opaque part of a facade, which include the life cycle of any material used in its construction: excavation, processing, construction, operation, maintenance, demolition and waste or recycling. With the aim of minimizing such embodied CO2 emissions, an integer linear programming problem is presented, in which CO2 emissions are minimized depending on other parameters involved in the construction of the facade, like the maximal thermal transmittance allowed by current legislation, thickness of the wall, budget, availability of materials for the different layers of the wall, etc. The paper also shows a case study based on a constructive solution for the opaque part of the envelope defined by up to six layers, with more than 1.1 million possible combinations. This case study considers seventy scenarios depending on maximal allowed thermal transmittances and thickness intervals for five different technologies applied to the structural element of the wall. Results show that an adequate selection of materials can reduce the embodied CO2 emissions of the opaque part of the envelope up to 78.5% for similar values of transmittance and thickness.

关键词： Embodied CO2 emissions Thermal transmittance Facade integer linear programming Minimization

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Edge metric dimensions via hierarchical product and integer linear programming

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OPTIMIZATION LETTERS 2021年第6期15卷 1993-2003页

作者： Klavzar, Sandi Tavakoli, Mostafa Univ Ljubljana Fac Math & Phys Ljubljana Slovenia Univ Maribor Fac Nat Sci & Math Maribor Slovenia Inst Math Phys & Mech Ljubljana Slovenia Ferdowsi Univ Mashhad Fac Math Sci Dept Appl Math POB 1159 Mashhad 91775 Razavi Khorasan Iran

If S = {v(1),..., v(k)} is an ordered subset of vertices of a connected graph G and e is an edge of G, then the vector r(G)(e vertical bar S) = (d(G)(v(1), e),..., d(G)(v(k), e)) is the edge metric S-representation of e. If the vertices of G have pairwise different edge metric S-representations, then S is an edge metric generator for G. The cardinality of a smallest edge metric generator is the edge metric dimension edim(G) of G. A general sharp upper bound on the edge metric dimension of hierarchical products G(U) Pi H is proved. Exact formula is derived for the case when vertical bar U vertical bar = 1. An integer linear programming model for computing the edge metric dimension is proposed. Several examples are provided which demonstrate how these two methods can be applied to obtain the edge metric dimensions of some applicable graphs.

关键词： Metric dimension Edge metric dimension Hierarchical product integer linear programming Molecular graph

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Static Mapping of Applications on Heterogeneous Multi-Core Platforms Combining Logic-Based Benders Decomposition with integer linear programming

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ACM TRANSACTIONS ON DESIGN AUTOMATION OF ELECTRONIC SYSTEMS 2018年第2期23卷 1–24页

作者： Emeretlis, Andreas Theodoridis, George Alefragis, Panayiotis Voros, Nikolaos Univ Patras VLSI Design Lab Dept Elect & Comp Engn Rion 26504 Greece Technol Educ Inst Western Greece Embedded Syst Design & Applicat Lab Comp & Informat Engn Dept Antirrio 30020 Greece

The proper mapping of an application on a multi-core platform and the scheduling of its tasks are key elements to achieve the maximum performance. In this article, a novel hybrid approach based on integrating the Logic-Based Benders Decomposition (LBBD) principle with a pure integer linear programming (ILP) model is introduced for mapping applications described by Directed Acyclic Graphs (DAGs) on platforms consisting of heterogeneous cores. The LBBD approach combines two optimization techniques with complementary strengths, namely ILP and Constraint programming (CP), and is employed as a cut generation scheme. The generated constraints are utilized by the ILP model to cut possible assignment combinations aiming at improving the solution or proving the optimality of the best-found one. The introduced approach was applied both on synthetic DAGs and on DAGs derived from real applications. Through the proposed approach, many problems were optimally solved that could not be solved by any of the above methods (ILP, LBBD) alone within a time limit of 2 hours, while the overall solution time was also significantly decreased. Specifically, the hybrid method exhibited speedups equal to 4.2 x for the synthetic instances and 10 x for the real-application DAGs over the LBBD approach and two orders of magnitude over the ILP model.

关键词： Task scheduling multi-core embedded platforms integer linear programming constraint programming Benders decomposition

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Redundancy allocation for series-parallel systems using integer linear programming

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IEEE TRANSACTIONS ON RELIABILITY 2008年第3期57卷 507-516页

作者： Billionnet, Alain Conservatoire Natl Arts & Metiers Comp Sci Lab CEDRIC Combinatorial Optimizat Grp Paris France

We consider the problem of maximizing the reliability of a series-parallel system given cost and weight constraints on the system. The number of components in each subsystem, and the choice of components are the-decision variables. In this paper, we propose an integer linear programming approach that gives an approximate feasible solution, close to the optimal solution, together with an upper bound on the optimal reliability. We show that integer linear programming is a useful approach for solving this reliability problem. The mathematical programming model is relatively simple. Its implementation is immediate by using a mathematical programming language, and integer linear programming software. And the computational experiments show that the performance of this approach is excellent based on a comparison with previous results.

关键词： computational experiments integer linear programming multiple component choices redundancy allocation system reliability

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Accurate Flow Decomposition via Robust integer linear programming

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2024年第6期21卷 1955-1964页

作者： Dias, Fernando H. C. Tomescu, Alexandru I. Aalto Univ Dept Math & Syst Anal Syst Anal Lab Espoo 02150 Finland Univ Helsinki Dept Comp Sci Helsinki 00100 Finland

Minimum flow decomposition (MFD) is a common problem across various fields of Computer Science, where a flow is decomposed into a minimum set of weighted paths. However, in Bioinformatics applications, such as RNA transcript or quasi-species assembly, the flow is erroneous since it is obtained from noisy read coverages. Typical generalizations of the MFD problem to handle errors are based on least-squares formulations or modelling the erroneous flow values as ranges. All of these are thus focused on error handling at the level of individual edges. In this paper, we interpret the flow decomposition problem as a robust optimization problem and lift error-handling from individual edges to solution paths. As such, we introduce a new minimum path-error flow decomposition problem, for which we give an integer linear programming formulation. Our experimental results reveal that our formulation can account for errors significantly better, by lowering the inaccuracy rate by 30-50% compared to previous error-handling formulations, with computational requirements that remain practical.

关键词： Bioinformatics Genomics RNA Splicing Assembly integer linear programming Sequential analysis Flow decomposition integer programming network flow uncertainty

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A 0-1 integer linear programming approach to schedule outages of nuclear power plants

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JOURNAL OF SCHEDULING 2013年第6期16卷 551-566页

作者： Jost, V. Savourey, D. Ecole Polytech LIX CNRS Palaiseau France

We address the problem of planning outages of nuclear power plants submitted by EDF (A parts per thousand lectricit, De France) as the challenge EURO/ROADEF 2010. As our team won the first prize of the contest in the senior category, our approach may be of interest: it is conceptually simple, easy to program and computationally relatively fast. We present both our method and some ideas to improve it.

关键词： Scheduling Energy integer linear programming Roadef challenge 0-1 programming

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Design of experiments and integer linear programming-assisted conjugate-gradient optimisation of high-κ/metal-gate nano-complementary metal-oxide semiconductor static random access memory

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IET COMPUTERS AND DIGITAL TECHNIQUES 2012年第4期6卷 240-248页

作者： Mohanty, S. P. Kougianos, E. Univ N Texas NanoSyst Design Lab Comp Sci & Engn Denton TX 76203 USA

Low-power consumption and stability in static random access memories (SRAMs) is essential for embedded applications. This study presents a novel design flow for power minimisation of nano-complementary metal-oxide semiconductor SRAMs, while maintaining stability. A 32 nm high-kappa/metal-gate SRAM has been used as an example circuit. The baseline circuit is subjected to power minimisation using a dual-threshold voltage assignment based on novel combined design of experiments and integer linear programming (DOE-ILP) approach. However, this leads to a 15% reduction in the static noise margin (SNM) of the cell. The conjugate gradient optimisation overcomes this SNM degradation, while reducing the power consumption. The final SRAM design shows 86% reduction in power consumption (including leakage) and 8% increase in the SNM compared with the baseline design. The variability analysis of the optimised cell is performed by considering the effect of 12 parameters. SRAM arrays of different sizes are constructed to demonstrate the feasibility of the proposed SRAM cell. To the best of the authors' knowledge, this is the first study which makes use of DOE-ILP and conjugate gradient method for simultaneous stability and power optimisation in high-kappa/metal-gate SRAM circuits.

关键词： linear programming SNM Optimisation techniques static random access memories integer linear programming Semiconductor storage gradient methods Memory circuits integer programming power consumption dual threshold voltage SRAM conjugate gradient optimisation high-κ/metal-gate nano-complementary metal-oxide semiconductor static random access memory static noise margin power minimisation baseline circuit SRAM chips

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Sparse Array Design via integer linear programming

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2024年 72卷 4812-4826页

作者： Zhuang, Yangjingzhi Zhang, Xuejing He, Zishu Greco, Maria Sabrina Gini, Fulvio Univ Elect Sci & Technol China Dept Informat & Commun Engn Chengdu 611731 Peoples R China Univ Pisa Dept Informat Engn I-56122 Pisa Italy

In this paper, a design framework based on integer linear programming is proposed for optimizing sparse array structures. We resort to binary vectors to formulate the design problem for non-redundant arrays (NRA) and minimum-redundant arrays (MRA). The flexibility of the proposed framework allows for dynamic adjustment of constraints to meet various applicative requirements, e.g., to achieve desired array apertures and mitigate mutual coupling effects. The proposed framework is also extended to the design of high-order arrays associated by exploiting high-order cumulants. The effectiveness of the proposed sparse array design framework is investigated through extensive numerical analysis. A comparative analysis with closed-form solutions and integer linear programming-based array design methods confirms the superiority of the proposed design framework in terms of number of degrees of freedom (DOF) and direction of arrival (DOA) estimation accuracy.

关键词： Sensor arrays Antenna arrays Mutual coupling Vectors Sensors Redundancy Apertures Non-redundant array minimum-redundant array sparse array design integer linear programming

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