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检索条件"主题词=pseudo-boolean optimization"

共 47 条记录，以下是31-40 订阅

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Decomposition of transition systems into sets of synchronizing Free-choice Petri Nets 25

Decomposition of transition systems into sets of synchronizi...

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25th Euromicro Conference on Digital System Design (DSD)

作者： Teren, Viktor Cortadella, Jordi Villa, Tiziano Univ Verona Dept Comp Sci Verona Italy Univ Politecn Cataluna Dept Comp Sci Barcelona Spain

ISBN: (纸本)9781665474047

Petri nets and transition systems are two important formalisms used for modeling concurrent systems. One interesting problem in this domain is the creation of a Petri net with a reachability graph equivalent to a given transition system. This paper focuses on the creation of a set of synchronizing Free-choice Petri nets (FCPNs) from a transition system. FCPNs are more amenable for visualization and structural analysis while not being excessively simple, as in the case of state machines. The results show that with a small set of FCPNs, the complexity of the model can be reduced when compared to the synthesis of a monolithic Petri net.

关键词： Transition system Petri net Free-choice Petri net decomposition theory of regions SAT pseudo-boolean optimization

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Optimizing One Million Variable NK Landscapes by Hybridizing Deterministic Recombination and Local Search 17

Optimizing One Million Variable NK Landscapes by Hybridizing...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Chicano, Francisco Whitley, Darrell Ochoa, Gabriela Tinos, Renato Univ Malaga Bulevar Louis Pasteur 35 Malaga 29071 Spain Colorado State Univ 1100 Ctr Ave Mall Ft Collins CO 80523 USA Univ Stirling Stirling FK9 4LA Scotland Univ Sao Paulo Av Bandeirantes 3900 BR-14040901 Ribeirao Preto SP Brazil

ISBN: (纸本)9781450349208

In gray-box optimization, the search algorithms have access to the variable interaction graph (VIG) of the optimization problem. For Mk Landscapes (and NK Landscapes) we can use the VIG to identify an improving solution in the Hamming neighborhood in constant time. In addition, using the VIG, deterministic Partition Crossover is able to explore an exponential number of solutions in a time that is linear in the size of the problem. Both methods have been used in isolation in previous search algorithms. We present two new gray-box algorithms that combine Partition Crossover with highly efficient local search. The best algorithms are able to locate the global optimum on Adjacent NK Landscape instances with one million variables. The algorithms are compared with a state-of-the-art algorithm for pseudo-boolean optimization: Gray-Box Parameterless Population Pyramid. Thee results show that the best algorithm is always one combining Partition Crossover and highly efficient local search. But the results also illustrate that the best optimizer differs on Adjacent and Random NK Landscapes.

关键词： Gray-box optimization pseudo-boolean optimization Partition Crossover Hamming Ball Hill Climber

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PBO-Based Test Compression 17

PBO-Based Test Compression

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17th Euromicro Conference on Digital System Design (DSD)

作者： Balcarek, Jiri Fiser, Petr Schmidt, Jan Czech Tech Univ Dept Digital Design CR-16635 Prague Czech Republic

ISBN: (纸本)9781479957934

This paper presents a novel ATPG and test compression algorithm based on pseudo-boolean (PBO) optimization. Similarly to SAT-based ATPGs, the test for each fault is represented implicitly as a PBO instance. The optimization process solves the problem of maximizing the number of unspecified values in the test. A novel don't care aware circuit-to-PBO conversion procedure is presented. The obtained unspecified values in the test are efficiently exploited in test compression. The produced compressed test sequence is suited for the RESPIN decompression architecture, thus for testing systems-on-chip. The presented experimental results show the efficiency and competitiveness of the proposed method.

关键词： ATPG test compression pseudo-boolean optimization SoC testing RESPIN

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Second Order Partial Derivatives for NK-landscapes 13

Second Order Partial Derivatives for NK-landscapes

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15th Genetic and Evolutionary Computation Conference (GECCO)

作者： Chen, Wenxiang Whitley, Darrell Hains, Doug Howe, Adele Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)9781450319638

Local search methods based on explicit neighborhood enumeration require at least O(n) time to identify all possible improving moves. For k-bounded pseudo-boolean optimization problems, recent approaches have achieved O(k(2) * 2(k)) runtime cost per move, where n is the number of variables and k is the number of variables per sub-function. Even though the bound is independent of n, the complexity per move is still exponential in k. In this paper, we propose a second order partial derivatives-based approach that executes first-improvement local search where the runtime cost per move is time polynomial in k and independent of n. This method is applied to NK-landscapes, where larger values of k may be of particular interest.

关键词： Local Search pseudo-boolean optimization Complexity per Move

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A Graph Coloring based Parallel Hill Climber for Large-scale NK-landscapes

A Graph Coloring based Parallel Hill Climber for Large-scale...

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2nd Genetic and Evolutionary Computation Conference (GECCO)

作者： Derbel, Bilel Canonne, Lorenzo Univ Lille CNRS INRIA Cent LilleUMR 9189CRIStAL F-59000 Lille France

ISBN: (纸本)9781450383509

Efficient hill climbers are at the heart of the latest gray-box optimization techniques, where some structural information about the optimization problem is available. Focusing on NK-landscapes as a challenging class of k-bounded pseudo-boolean functions, we propose a quality-enhanced and a time-accelerated hill climber. Our investigations are based on the idea of performing several simultaneous moves at each iteration of the search process. This is enabled using graph coloring to structure the interacting variables of an NK-landscape, and to identify subsets of possibly improving independent moves in the Hamming distance 1 neighborhood. Besides being extremely competitive with respect to the state-of-the-art first- and best- ascent serial variants, our initial design exposes a natural degree of parallelism allowing us to convert our serial algorithm into a parallel hill climber without further design efforts. As such, we also provide a multi-threaded implementation using up to 10 shared-memory CPU-cores. Using a range of large-scale random NK-landscapes with up to 10(6) variables, we provide evidence on the efficiency and effectiveness of the proposed hill climber and we highlight the strength of our parallel design in attaining substantial acceleration factors for the largest experimented functions.

关键词： Graybox optimization Hill Climbing NK-landscapes pseudo-boolean optimization Multi-threaded Algorithms

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Efficient Identification of Improving Moves in a Ball for pseudo-boolean Problems 14

Efficient Identification of Improving Moves in a Ball for Ps...

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16th Genetic and Evolutionary Computation Conference (GECCO)

作者： Chicano, Francisco Whitley, Darrell Sutton, Andrew M. Univ Malaga Dept Lenguajes & Ciencias Computac Andalucia Tech E-29071 Malaga Spain Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA Univ Jena Fak Math & lnformat D-07743 Jena Germany

ISBN: (纸本)9781450326629

Hill climbing algorithms are at the core of many approaches to solve optimization problems. Such algorithms usually require the complete enumeration of a neighborhood of the current solution. In the case of problems defined over binary strings of length n, we define the r-ball neighborhood as the set of solutions at Hamming distance r or less from the current solution. For r << n this neighborhood contains Theta (n(r)) solutions. In this paper efficient methods are introduced to locate improving moves in the r-ball neighborhood for problems that can be written as a sum of a linear number of subfunctions depending on a bounded number of variables. NK-landscapes and MAX-kSAT are examples of these problems. If the number of subfunctions depending on any given variable is also bounded, then we prove that the method can explore the neighborhood in constant time, despite the fact that the number of solutions in the neighborhood is polynomial in n. We develop a hill climber based on our exploration method and we analyze its efficiency and efficacy using experiments with NKq-landscapes instances.

关键词： Theory Algorithms Hill Climbing Local Search NK-landscapes pseudo-boolean optimization

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Algebraic Side-Channel Analysis in the Presence of Errors

Algebraic Side-Channel Analysis in the Presence of Errors

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12th International Workshop on Cryptographic Hardware and Embedded Systems (CHES 2010)

作者： Oren, Yossef Kirschbaum, Mario Popp, Thomas Wool, Avishai Tel Aviv Univ Comp & Network Secur Lab Sch Elect Engn IL-69978 Ramat Aviv Israel Graz Univ Technol Inst Appl Informat Proc & Commun A-8010 Graz Austria

ISBN: (纸本)9783642150302

Measurement errors make power analysis attacks difficult to mount when only a single power trace is available: the statistical methods that make DPA attacks so successful are not applicable since they require many (typically thousands) of traces. Recently it was suggested by [18] to use algebraic methods for the single-trace scenario, converting the key recovery problem into a boolean satisfiability (SAT) problem, then using a SAT solver. However, this approach is extremely sensitive to noise (allowing an error rate of well under 1% at most), and the question of its practicality remained open. In this work we show how a single-trace side-channel analysis problem can be transformed into a pseudo-boolean optimization (PBOPT) problem, which takes errors into consideration. The PBOPT instance can then be solved using a suitable optimization problem solver. The PBOPT syntax provides for a more expressive input specification which allows a very natural representation of measurement errors. Most importantly, we show that using our approach we are able to mount successful and efficient single-trace attacks even in the presence of realistic error rates of 10%-20%. We call our new attack methodology Tolerant Algebraic Side-Channel Analysis (TASCA). We show practical attacks on two real ciphers: Keeloq and AES.

关键词： Algebraic attacks power analysis side-channel attacks pseudo-boolean optimization

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On Dedicated CDCL Strategies for PB Solvers 24th

On Dedicated CDCL Strategies for PB Solvers

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24th International Conference on Theory and Applications of Satisfiability Testing (SAT)

作者： Le Berre, Daniel Wallon, Romain Univ Artois Ctr Rech Informat Lens CRIL CNRS F-62300 Lens France Ecole Polytech X Uber Chair Lab Informat X F-91120 Palaiseau France

ISBN: (纸本)9783030802233;9783030802226

Current implementations of pseudo-boolean (PB) solvers working on native PB constraints are based on the CDCL architecture which empowers highly efficient modern SAT solvers. In particular, such PB solvers not only implement a (cutting-planes-based) conflict analysis procedure, but also complementary strategies for components that are crucial for the efficiency of CDCL, namely branching heuristics, learned constraint deletion and restarts. However, these strategies are mostly reused by PB solvers without considering the particular form of the PB constraints they deal with. In this paper, we present and evaluate different ways of adapting CDCL strategies to take the specificities of PB constraints into account while preserving the behavior they have in the clausal setting. We implemented these strategies in two different solvers, namely Sat4j (for which we consider three configurations) and RoundingSat. Our experiments show that these dedicated strategies allow to improve, sometimes significantly, the performance of these solvers, both on decision and optimization problems.

关键词： pseudo-boolean solving pseudo-boolean optimization Branching heuristics Learned constraint deletion strategies Restart policies

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Enhancing Partition Crossover with Articulation Points Analysis 18

Enhancing Partition Crossover with Articulation Points Analy...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Chicano, Francisco Ochoa, Gabriela Whitley, Darrell Tinos, Renato Univ Malaga Malaga Spain Univ Stirling Stirling Scotland Colorado State Univ Ft Collins CO 80523 USA Univ Sao Paulo Ribeirao Preto SP Brazil

ISBN: (纸本)9781450356183

Partition Crossover is a recombination operator for pseudo-boolean optimization with the ability to explore an exponential number of solutions in linear or square time. It decomposes the objective function as a sum of subfunctions, each one depending on a different set of variables. The decomposition makes it possible to select the best parent for each subfunction independently, and the operator provides the best out of 2q solutions, where q is the number of sub-functions in the decomposition. These subfunctions are defined over the connected components of the recombination graph: a subgraph of the objective function variable interaction graph containing only the differing variables in the two parents. In this paper, we advance further and propose a new way to increase the number of linearly independent subfunctions by analyzing the articulation points of the recombination graph. These points correspond to variables that, once flipped, increase the number of connected components. The presence of a connected component with an articulation point increases the number of explored solutions by a factor of, at least, 4. We evaluate the new operator using Iterated Local Search combined with Partition Crossover to solve NK Landscapes and MAX-SAT.

关键词： Partition Crossover Gray-box optimization articulation points pseudo-boolean optimization

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Positive half-products and scheduling with controllable processing times

Positive half-products and scheduling with controllable proc...

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8th International Workshop on Project Management and Scheduling

作者： Janiak, A Kovalyov, MY Kubiak, W Werner, F Mem Univ Newfoundland Fac Business Adm St John NF A1B 3X5 Canada Wroclaw Univ Technol Inst Engn Cybernet Wroclaw Poland Belarusian State Univ Fac Econ Minsk 220050 BELARUS Natl Acad Sci Belarus United Inst Informat Problems Minsk 220050 BELARUS Otto Von Guericke Univ Magdeburg Germany

We study the single machine scheduling problem with controllable job processing times to minimize a linear combination of the total weighted job completion time and the total weighted processing time compression. We show that this scheduling problem is a positive half-product minimization problem. Positive half-products make up an interesting subclass of half-products and are introduced in this paper to provide a conceptual framework for the problem with controllable job processing times as well as other problems. This framework allows to readily derive in one fell swoop a number of results for the problem with controllable processing times from more general results obtained earlier for the half-product. We also present fast fully polynomial time approximation schemes for the problem with controllable processing times. The schemes apply to all positive half-products. (c) 2004 Elsevier B.V. All rights reserved.

关键词： single machine scheduling controllable processing times pseudo-boolean optimization fully polynomial time approximation scheme computational complexity

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