Search Results - (( using function _ algorithm ) OR ( software optimization problem algorithm ))

Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

“…To solve this issues, multi-objective genetic algorithm was chosen as the methodology for this project, specifically using NSGA-ii algorithm. …”
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Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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Assessment of metaheuristic algorithms to optimize of mixed-model assembly line balancing problem with resource constraints by M.M., Razali, M. F. F., Ab Rashid, M. R. A., Make

“…In this study, an assessment of metaheuristic algorithms to optimize MMALBP was conductedby using four popular metaheuristics , namely particle swarm optimization (PSO), simulated annealing (SA), ant colony optimization (ACO),and genetic algorithm (GA). …”
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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

“…Owing to the fact that they are new and much of their relative performance are still unknown (as compared to other established meta-heuristic algorithms), Bacterial Foraging Optimization Algorithm (BFO) and Bat Algorithm (BA) have been adopted for comparison using the 12 selected benchmark functions. …”
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African Buffalo Optimization by Odili, Julius Beneoluchi, M. N. M., Kahar

“…This paper presents an overview of major metaheuristic algorithms with the aim of providing a basis for the development of the African Buffalo Optimization algorithm which is a nature-inspired, population-based metaheuristic algorithm. …”
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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

“…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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A carnivorous plant algorithm for solving global optimization problems by Ong, Kok Meng, Ong, Pauline, Sia, Chee Kiong

“…Its convergence characteristic and computational time were analysed and compared with seven widely used metaheuristic algorithms, with the superiority was validated using the Wilcoxon signed-rank test. …”
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Comparative implementation of the benchmark Dejong 5 function using flower pollination algorithm and the African buffalo optimization by Odili, Julius Beneoluchi, Noraziah, Ahmad

“…In addition, it explores the Dejong 5 function with the hope of attracting the attention of the research community to evaluate the capacity of the two comparative algorithms as well as the Dejong 5 function. …”
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Hybrid harmony search algorithm for continuous optimization problems by Ala’a Atallah, Hamad Alomoush

“…The first benchmarking set consists of 24 classical benchmark unimodal and multimodal functions whilst the second benchmark set contains 30 state-of-the-art benchmark functions from the Congress on Evolutionary Computation (CEC). …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…GWO-HS was evaluated using 24 classical benchmark functions with 30 state-of-the-art benchmark functions from CEC2014. …”
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System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

“…The minimization of system execution and transfer time in the proposed algorithm are considered as objective functions. The experimental testing of the proposed algorithm are considered as objective functions. …”
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Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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A Comparison of Particle Swarm optimization and Global African Buffalo Optimization by Adam Kunna Azrag, Mohammed, Tuty Asmawaty, Abdul Kadir, Noorlin, Mohd Ali

“…The experimental results illustrated the differences in the performances of both algorithms toward the optimum solution. At the end of the experiments, the PSO algorithm quickly convergence towards the optimum solution using a few particles and iterations rather than GABO. …”
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Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh by Hisham Ahmad, Theeb Shehadeh

“…The SSO is tested with several benchmark functions used in the area of optimization. The obtained results are compared with the results of four algorithms. …”
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Solving 0/1 Knapsack Problem Using Hybrid HS and Jaya Algorithms by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

“…HS algorithm has been modified to handle the 0/1 Knapsack problem, such as adding penalty function to cope the weight condition, exclude the harmony search bandwidth (bw) parameter, and use the current best result in the next iteration to obtain a better result. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

“…For illustration, an economic growth problem is solved by using the algorithm proposed. The results obtained demonstrate the efficiency of the algorithm proposed. …”
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Optimal power flow using hybrid firefly and particle swarm optimization algorithm by Khan, Abdullah, Hizam, Hashim, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi

“…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems by Alomoush, Alaa A., Alsewari, Abdulrahman A., Kamal Z., Zamli, Alrosan, Ayat, Alomoush, Waleed, Alissa, Khalid

“…A convergence rate graph is also used to show the overall performance of the new algorithms.…”
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