Search Results - (( parallel optimization based algorithm ) OR ( process optimization parallel algorithm ))
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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Thesis -
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A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)
Published 2013“…One of the popular ways to speed up the processing time was by running them as parallel. The idea of parallel GAs may refer to an algorithm that works by dividing large problem into smaller tasks. …”
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Conference or Workshop Item -
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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4
Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…Eventually, the workflow is executed. The second algorithm is a variation in first algorithm in which data parallelism is introduced in each partition. …”
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5
Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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Parallel multiple tabu search for multiobjective Urban Transit Scheduling Problem
Published 2020“…A set covering model was then adopted to minimize the number of buses and drivers simultaneously. A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. …”
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Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…In addition, a distributed environment is set up to conduct parallel optimization of the proposed method so that multi-local optimizations could be performed simultaneously. …”
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FPGA implementation of metaheuristic optimization algorithm
Published 2023“…Metaheuristic algorithms are gaining popularity amongst researchers due to their ability to solve nonlinear optimization problems as well as the ability to be adapted to solve a variety of problems. …”
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Fpga Implementation Of Metaheuristic Optimization Algorithm
Published 2022“…Metaheuristic algorithms are gaining popularity amongst researchers due to their ability to solve nonlinear optimization problems as well as the ability to be adapted to solve a variety of problems. …”
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Undergraduates Project Papers -
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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Monograph -
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…The base learners adopt a hybrid Back-Propagation (BP) and Particle Swarm Optimization (PSO) algorithms to exploit the corresponding local and global optimization capabilities for identifying optimal features and improving FDD performance. …”
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…Modification and simplification using parallel processing are done for both methods to grossly search the optimal solution and to minimize the program running time, respectively. …”
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Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz
Published 2017“…Parking space are designed based on the three type which are parallel, diagonal, and perpendicular. …”
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Optimizing OLAP heterogeneous computing based on Rabin-Karp algorithm
Published 2013“…In this paper, through experimental results and based on Rabin-Karp Algorithm; we propose an optimized heterogeneous solution that takes into account the benefits and the boundaries in order to achieve a better OLAP performance in terms of response time with three times gain. …”
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Proceeding Paper -
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Design and development of high performance swa cell design for local DNA sequence alignment
Published 2017“…This study proposed three new DNA sequence alignment accelerator system cell design and architecture based on the Smith-Waterman Algorithm (SWA) named as the new Optimized SWA Linear Gap Penalty (OSL), Optimized SWA Affine Gap Penalty (OSA), and Optimized Recursive Variable Expansion SWA Linear Gap Penalty (ORSL). …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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