Search Results - (( simulation optimization using algorithm ) OR ( problem implementation 5s algorithm ))

FPGA implementation of metaheuristic optimization algorithm by Nurul Hazlina, Noordin, Phuah, Soon Eu, Zuwairie, Ibrahim

“…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 by Phuah, Soon Eu

“…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 Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

“…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. Input parameters, the number of fireflies, and the number of function evaluations were determined before the implementation of the firefly algorithm to solve formulated problems. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…Based on literature, stereo algorithm is already being implemented to solve the distance measurement problem. …”
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

“…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
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Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems by Uwaechia, Anthony Ngozichukwuka

“…Simulation results demonstrate that the proposed CoFA and SdMP algorithms for CE have around 11.1%, 18.3%, 28.9% and 42.8% and around 5.6%, 13.9%, 22.8% and 33.3% performance improvement at MSE value of 2 × 10−3 when compared to FACS, gOMP, OMP and ROMP algorithms, respectively. …”
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Ant Colony Optimization for Solving Solid Waste Collection Scheduling Problems by Ismail, Zuhaimy, Loh, Ser Lee

“…For comparison purposes, Simulated Annealing (SA) was used to generate the solution under the same condition. …”
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Ant colony optimization for solving solid waste collection scheduling problems by Ismail, Zuhaimy, Loh, S. L.

“…For comparison purposes, Simulated Annealing (SA) was used to generate the solution under the same condition. …”
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An Application of Grey Wolf Optimizer for Solving Combined Economic Emission Dispatch Problems by Hong, Mee Song, M. H., Sulaiman, Mohd Rusllim, Mohamed

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Battery energy storage system sizing using PSO algorithm in DIgSILENT powerfactory by Gan, Chin Kim, Tan, Pi Hua, Al-Areqi, Khaldon Ahmed Qaid, Tee, Wei Hown

“…Problem for optimization of BESS sizing and placement are formulated in DPL script with analytic algorithm and particle swarm optimization (PSO) with loadflow simulation. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

“…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”

OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour, Masoud, Ali, Zaipatimah, Othman, Muhammad Murtadha, Bo, Rui, Javadi, Mohammad Sadegh, Ridha, Hussein Mohammed, Alrifaey, Moath

“…The proposed approach is tested and validated on IEEE 57-bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

“…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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Coordinated and optimal voltage control for voltage regulation using firefly algorithm by Kamarudin M.N., Hashim T.J.T.

“…Firefly Algorithm (FA) which is a known heuristic optimization technique for finding the optimal solution is used in this work. …”

Optimization of substation grounding grid design for horizontal and vertical multilayer and uniform soil condition using Simulated Annealing method by Permal N., Osman M., Ariffin A.M., Boopalan N., Abidin Ab Kadir M.Z.

Efficient relay placement algorithm using landscape aware routing (erpalar) by Onabajo, Olawale Olusegun

“…GA is an optimization algorithm that simulates natural selection process as found in nature. …”
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Memory efficient BFGS neural-network learning algorithms using MLP-network: a survey by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

“…Simulation results using a control benchmark problems show that OM BFGS, which is mathematically equivalent to full memory (FM) BFGS training when there are no constraints on memory, have performance gain compared to other memory efficient BFGS training algorithms.…”
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Deterministic static sensor node placement in wireless sensor network based on territorial predator scent marking behavior by Abidin H.Z., Din N.M., Radzi N.A.M.

“…This paper proposes a sensor node placement algorithm that utilizes a new biologically inspired optimization algorithm that imitates the behaviour of territorial predators in marking their territories with their odours known as Territorial Predator Scent Marking Algorithm (TPSMA). …”