Search Results - (( simulation optimization methods algorithm ) OR ( parallel evaluation case algorithm ))
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1
Dynamic partitioning and data allocation method on heterogeneous architecture / Muhammad Helmi Rosli
Published 2015“…Each experiment highlight the advantages and disadvantages of the experimental architecture.The disadvantages from each experiment prompts the design of dynamic parallel partitioning and allocating framework. The case study use for this experiment is Sobel edge detection algorithm. …”
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Thesis -
2
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
3
Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations
Published 2004“…All the numerical results are given to illustrate the algorithms developed for the cases that we were tested. …”
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4
Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil
Published 2014“…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
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5
Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
6
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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7
A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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8
Route optimization using shortest path method / Muhamad Faisal Amin Shakri
Published 2025“…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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9
Improved particle swarm optimization by fast annealing algorithm
Published 2019“…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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Proceeding Paper -
10
Asynchronous simulated kalman filter optimization algorithm
Published 2018“…Simulated Kalman filter (SKF) is an optimization algorithm which is inspired by Kalman filtering method. …”
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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…Similarly, when data parallelism is introduced in the algorithm the performance of the algorithm improved further by 12% in latency and 17% in throughput when compared to PDWA algorithm. …”
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12
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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13
Optimization of milling parameters using ant colony optimization
Published 2008“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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Undergraduates Project Papers -
14
Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem
Published 2008“…Genetic Algorithm as population-based methods are better identifying promising areas in the search space, while Tabu Search and Simulated Annealing as trajectory methods are better in exploring promising areas in search space. …”
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Monograph -
15
Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. …”
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Conference or Workshop Item -
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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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17
An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system
Published 2018“…This paper reports the first attempt to tune gain values in proportional-integral-derivative (PID) controllers using an optimizer called simulated Kalman filter (SKF) algorithm. …”
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Conference or Workshop Item -
18
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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19
Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…Majority of the research works in this project were in CAE software environment and method to implement optimization to 1D engine simulation. …”
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Proceeding Paper -
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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