Search Results - (( processes optimization _ algorithm ) OR ( parallel optimization based algorithm ))
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1
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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Thesis -
2
Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…This thesis proposes data-intensive workflow optimization algorithms. The first algorithm architecture consists of two phases a) workflow partitioning, and b) partitions mapping. …”
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3
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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4
A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)
Published 2013“…Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. …”
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5
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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6
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 -
7
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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8
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…Therefore, this study explores how to model reconfigurable manufacturing activities in an optimization perspective and how to develop and select appropriate non-conventional optimization techniques for reconfigurable process planning.In this study, a new approach to modeling Manufacturing Process Planning Optimization (MPPO) was developed by extending the concept of manufacturing optimization through a decoupled optimization method. …”
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9
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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10
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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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization
Published 2024Subjects: “…Optimization algorithms (Computer science)…”
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12
Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…The optimum parameters were determined according to the design flow, constraints value and mathematical algorithm. Based on MOGA-II analysis, every workflow generated 1600 feasible solutions for optimization that meet the design space requirement. …”
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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 -
14
Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz
Published 2017“…Therefore, framework development methodology is used to make sure the system successful and can be developed according to the schedule. Genetic algorithm is chosen for the development of the prototype to prove that genetic algorithm is the best technique to implement for optimization. …”
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15
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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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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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…Future work entails enhancing system robustness through comprehensive contingency planning, real-time data integration, and algorithmic optimization, with a focus on refining the genetic algorithm and exploring parallel processing techniques to further enhance efficiency and scalability.…”
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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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Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing
Published 2013“…Performance of the QPSO technique based on many heuristic algorithms it is comprised the following steps. …”
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20
Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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