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...
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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.
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 mainta...
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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 proact...
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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.
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...
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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.
An Improved Evolution Algorithm (IEA) is proposed in this paper. It has some new features: 1) using multi-parent search strategy and stochastic ranking strategy and a simple diversity rules to maintain the diversity o...
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Recovery of sparse signals from linear measurements arises in several signal processing applications. Basis pursuit is a standard convex optimization program, often used to perform this task. In this paper we present ...
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ISBN:
(纸本)9781424451807
Recovery of sparse signals from linear measurements arises in several signal processing applications. Basis pursuit is a standard convex optimization program, often used to perform this task. In this paper we present two algorithms to dynamically update the solution of basis pursuit as 1) new measurements are sequentially added or 2) the underlying signal changes slightly. The goal is to avoid solving the (computationally expensive) optimization routine every time a small change occurs in the measurements. Our proposed update algorithms are based on homotopy principles, which iteratively update the solution by moving from an already solved problem towards the desired problem. Each homotopy step involves only a few matrix-vector multiplications. Simulation results show that the number of homotopy steps required for the update is comparable to the sparsity of the underlying signals.
Particle Swarm optimization (PSO) has shown its good performance on well-known numerical function problems. However, on some multimodal functions the PSO easily suffers from premature convergence because of the rapid ...
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The proceedings contain 6 papers. The topics discussed include: FPGA-based acceleration of CHARMM-potential minimization;an integrated reduction technique for a double precision accumulator;SCF: a device- and language...
ISBN:
(纸本)9781605587219
The proceedings contain 6 papers. The topics discussed include: FPGA-based acceleration of CHARMM-potential minimization;an integrated reduction technique for a double precision accumulator;SCF: a device- and language-independent task coordination framework for reconfigurable, heterogeneous systems;a framework for core-level modeling and design of reconfigurable computing algorithms;sorting on architecturally diverse computer systems;and bridging parallel and reconfigurable computing with multilevel PGAS and SHMEM+.
As the matter of the developing of the intelligent system, the intelligent systems have more and more subsystems and elements to support or to control the system functions. Therefore, building an advanced intelligent ...
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The proceedings contain 634 papers. The topics discussed include: a gait recognition method based on KFDA and SVM;a general QoS-aware service composition model for ubiquitous computing;a hybrid approach of path planni...
ISBN:
(纸本)9781424438945
The proceedings contain 634 papers. The topics discussed include: a gait recognition method based on KFDA and SVM;a general QoS-aware service composition model for ubiquitous computing;a hybrid approach of path planning for mobile robots based on the combination of ACO and APF algorithms;a hybrid genetic algorithm with hyper-mutation and elitist strategies for automated analog circuit design;a hybrid particle swarm optimization algorithm for multimodal function optimization;an algorithm of coalition structure generation with given required bound based on cardinality structure;an adaptive weighted support vector machine;an adaptive repulsive particle swarm optimization for make span and maximum lateness minimization in the permutation flowshop scheduling problem;and an adaptive clonal selection algorithm and its applications.
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