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6th international Conference on Soft Computing and Pattern Recognition (SoCPaR)

作者： Sandeli, Mohamed Batouche, Mohamed Univ Constantine 2 Fac NTIC Software & Informat Technol Dept Constantine Algeria Univ Constantine 2 Fac NTIC Comp Sci & Applicat Dept Constantine Algeria

ISBN: (纸本)9781479959341

Image segmentation is a platform for many high-level applications. It aims to identify the different homogeneous regions of an image. In our work, we cast the problem as a parallel distributed optimization task and we present a new method for image segmentation by multilevel thresholding based on generalized island model (GIM). This model is characterized by the cooperation of three metaheuristics namely Particle Swarm optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC). The cooperation is ensured by the use of a migration pattern the purpose of which is to avoid getting stuck in local optima. The effectiveness of the proposed method has been assessed and compared to each of the algorithms of the GIM model when used separately and other methods from the literature like Darwinian PSO (DPSO), Fractional-Order Darwinian PSO (FO-DPSO). The obtained results are very promising and show the positive impact of the use of a parallel distributed model. They also show that the proposed method competes and even outperforms the other methods.

关键词： Image segmentation Generalized Island Model multilevel thresholding Metaheuristics Parallel Distributed optimization

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PARMETAOPT - Parallel Metaheuristics Framework for Combinatorial optimization Problems

PARMETAOPT - Parallel Metaheuristics Framework for Combinato...

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5th IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems - Technology and applications (IDAACS)

作者： Borovska, Plamenka Nakov, Ognian Lazarova, Milena Tech Univ Sofia Dept Comp Syst Sofia 1000 Bulgaria

ISBN: (纸本)9781424448814

The paper presents an experimental parallel metaheuristics framework for solving combinatorial optimization of grand challenge scientific and engineering problems that has been developed based on biologically inspired metaheuristics, modeling of social behavior and cultural evolution as well as trajectory-based methods. A prototype class library for metaheuristics is developed and several parallel computational models of metaheuristics for solving combinatorial optimization problems are implemented. The library contains implementations in C++ of parallel computational models for both population based and trajectory based metaheuristics. Some improvements in the parallel models are suggested and implemented in the library PARMETAOPT. The influence of the parameters on the performance of some of the parallel algorithms is analyzed using the developed parallel metaheuristics framework and performance tuning rules are suggested. The implementations are based on message passing with MPICH2 for the flat programming models and OpenMP API is used for multithreading in the hybrid programming models.

关键词： metaheuristics class libraries optimization problems near-optimal solution parallel computational model message passing multithreading

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Introducing an FPGA based - genetic algorithms in the applications of blind signals separation 3

Introducing an FPGA based - genetic algorithms in the applic...

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3rd IEEE international workshop on System-on-Chip for Real-Time applications

作者： Emam, H Ashour, MA Fekry, H Wahdan, AM NCRRT Atom Energy Auth Cairo Egypt

ISBN: (纸本)076951944X

Genetic algorithms (GAs) are one of the most advanced optimization techniques. The main objective of this paper, is introducing an FPGA implementation based genetic algorithm, then applying it, as an adaptive algorithm, on a non-linear adaptive filters for the purpose of blind signals separation. In this case, the non-linear estimator has been used to predict the error filter and GA will be used to optimize the filter coefficients through the search for a near optimum solution. The proposed Hardware Genetic algorithms (HGA) has been presented and tested, first, by different sine wave signals, then by audio wave signals to judge the design separation capability. The implementation results declare that HGA approach significantly enhances the system performance as a step toward real time performance.

关键词： genetic algorithms field programmable gate array (FPGA) digital signal processing blind signal separation

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Model and extended Kuhn-Tucker approach for bilevel multi-follower decision making in a referential-uncooperative situation

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JOURNAL OF GLOBAL optimization 2007年第4期38卷 597-608页

作者： Lu, Jie Shi, Chenggen Zhang, Guangquan Dillon, Tharam Univ Technol Sydney Fac Informat Technol Sydney NSW 2007 Australia

When multiple followers are involved in a bilevel decision problem, the leader's decision will be affected, not only by the reactions of these followers, but also by the relationships among these followers. One of the popular situations within this bilevel multi-follower issue is where these followers are uncooperatively making their decisions while having cross reference to decision information of the other followers. This situation is called a referential-uncooperative situation in this paper. The well-known Kuhn-Tucker approach has been previously successfully applied to a one-leader-and-one-follower linear bilevel decision problem. This paper extends this approach to deal with the above-mentioned linear referential-uncooperative bilevel multi-follower decision problem. The paper first presents a decision model for this problem. It then proposes an extended Kuhn-Tucker approach to solve this problem. Finally, a numerical example illustrates the application of the extended Kuhn-Tucker approach.

关键词： bilevel programming bilevel multi-follower decision Kuhn-Tucker approach optimization

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optimization of scheduling problem for auto mixed model assembly line

Optimization of scheduling problem for auto mixed model asse...

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2009 international workshop on Intelligent Systems and applications, ISA 2009

作者： Sun, Hu Xu, Linwei School of Logistics Engineering Wuhan University of Technology WHUT Wuhan China

ISBN: (纸本)9781424438945

The scheduling of the mixed model assembly line is an important problem in JIT production. The multistage scheduling model of a auto vehicle mixed model assembly line is established. The goal of the model is to maintain the consumption of the parts of components at various working procedures in the production line uniform as much as possible. And the goal is solved by Lingo optimization software. The contrastive analysis indicates that the result obtained by this model surpasses many algorithms, such as goal follows algorithms, genetic algorithm, simulation annealing algorithm, and so on. © 2009 IEEE.

关键词： Scheduling

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Selection of redundant and non redundant optimization structures in VLDBs

Selection of redundant and non redundant optimization struct...

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18th international Conference on Database and Expert Systems applications

作者： Bellatreche, Ladjel Univ Poitiers ENSMA LISI F-86961 Poitiers France

ISBN: (纸本)9780769529325

Very large database applications are usually modelled using huge schemas with several large tables with many columns. Queries defined on those schemas are complex since they contain join and aggregation operations. In large databases, join operations are the most used and the most expensive, especially when the size of tables is very large. To optimize these complex queries, several optimization structures have been proposed. Selecting any optimization structure is NP-hard problems since their search spaces are very large. In this paper, we classify these structures into two main categories: (1) non redundant structures (horizontal and vertical partitioning, parallel processing) and (2) redundant structures (materialized views, indexing schemes). Our study focuses on two non redundant structures: horizontal and vertical partitioning and one redundant structure: bitmap join indexes, where formalizations of their selection problems and algorithms are presented. We propose an approach combining horizontal partitioning and bitmap join indexes to speed up queries and to reduce storage and maintenance costs of indexes. Finally, our proposed algorithms are validated using experimental studies.

关键词： Structural optimization

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Proactive Monitoring of Security Policy Accomplishment in Computer Networks

Proactive Monitoring of Security Policy Accomplishment in Co...

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5th IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems - Technology and applications (IDAACS)

作者： Kotenko, Igor Bogdanov, Vitaly St Petersburg Inst Informat & Automat St Petersburg Russia

ISBN: (纸本)9781424448814

One of topical tasks of policy-based security management is checking that the security policy stated in organization corresponds to its implementation in the computer network. The paper considers an approach to proactive monitoring of security policy performance and security mechanisms functioning. This approach is based on different strategies of automatic imitation of possible users' actions in the computer network, including exhaustive search, express-analysis and generating the optimized test sequences. It is applicable to different security policies. The paper describes stages, generalized algorithms and main peculiarities of the suggested approach and formal methods used to fulfill the test sequence optimization. We consider the generalized architecture of the proactive monitoring system "Proactive security scanner" (PSC) developed and its implementation.

关键词： Homeland Security Security and Reliability Security policy monitoring Test sequence optimization

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Multiple Periods Location and Capacity optimization of Charging Stations for Electric Vehicle

Multiple Periods Location and Capacity Optimization of Charg...

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China-Qatar international workshop on Artificial Intelligence and applications to Intelligent Manufacturing (AIAIM)

作者： Hu, Dandan Liu, Zhi-Wei Chi, Ming South Cent Univ Nationalities Sch Management Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Dept Automat Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9781538664452

With rapid growth of electric vehicles, the development of charging stations has to keep up. This paper proposes a multi-period location and capacity optimization model of charging stations, and introduces congestion rate to control the queuing situation. As the model is a NP-hard problem, two kinds of greedy algorithms are proposed, which are proved to be effective by lots of computational experiments.

关键词： charging station location capacity multi-period heuristic

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optimization of a multilevel Checkpoint Model with Uncertain Execution Scales 14

Optimization of a Multilevel Checkpoint Model with Uncertain...

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international Conference on High Performance Computing, Networking, Storage and Analysis

作者： Di, Sheng Bautista-Gomez, Leonardo Cappello, Franck INRIA Rocquencourt France Argonne Natl Lab Argonne IL 60439 USA Univ Illinois Urbana IL USA

ISBN: (纸本)9781479955008

Future extreme-scale systems are expected to experience different types of failures affecting applications with different failure scales, from transient uncorrectable memory errors in processes to massive system outages. In this paper, we propose a multilevel checkpoint model by taking into account uncertain execution scales (different numbers of processes/cores). The contribution is threefold: (1) we provide an in-depth analysis on why it is difficult to derive the optimal checkpoint intervals for different checkpoint levels and optimize the number of cores simultaneously;(2) we devise a novel method that can quickly obtain an optimized solution-the first successful attempt in multilevel checkpoint models with uncertain scales;and (3) we perform both large-scale real experiments and extreme-scale numerical simulation to validate the effectiveness of our design. The experiments confirm that our optimized solution outperforms other state-of- the-art solutions by 4.3-88% on wall-clock length.

关键词： checkpointing multiprocessing systems numerical analysis optimisation checkpoint levels extreme-scale numerical simulation extreme-scale systems failure scales massive system outages multilevel checkpoint model optimal checkpoint intervals optimization processes/cores transient uncorrectable memory errors uncertain execution scales wall-clock length Analytical models Approximation algorithms Computational modeling Equations Heating Mathematical model optimization Multiprocessing systems checkpointing Approximation algorithms ANALYSIS MODELS Computational modeling Cell Cycle Checkpoints Checkpoints Mathematical Model Numerical Analysis Dermal denticles Heating Plant uncertain BALANCES multilayers

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Some methods for evaluating the optimality of elements in matroids with ill-known weights

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FUZZY SETS AND SYSTEMS 2009年第10期160卷 1341-1354页

作者： Fortin, Jerome Kasperski, Adam Zielinski, Pawel Wroclaw Univ Technol Inst Math & Comp Sci PL-50370 Wroclaw Poland Univ Toulouse 3 Inst Rech Informat Toulouse F-31062 Toulouse 4 France Wroclaw Univ Technol Inst Ind Engn & Management PL-50370 Wroclaw Poland

In this paper a class of matroidal combinatorial optimization problems with imprecise weights of elements is considered. The imprecise weights are modeled by intervals and fuzzy intervals. The concepts of possible and necessary optimality under imprecision are recalled. Some efficient methods for evaluating the possible and necessary optimality of elements in the interval-valued problems are proposed. Some efficient algorithms for computing the exact degrees of possible and necessary optimality of elements in the fuzzy-valued problems are designed. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Matroid Fuzzy interval Possibility theory Combinatorial optimization Gradual number

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