Search Results - (( simulation optimization task algorithm ) OR ( using function _ algorithm ))

Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application by Hardhienata, Medria Kusuma Dewi, Priandana, Karlisa, Putra, Daffa Rangga, Sriatun, Mamiek, Wulandari, Buono, Agus, Mohamed, Raihani

“…By employing such a function, simulation results show that the total resource used by the agents and total communication cost can be optimized. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

“…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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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

“…Mixed-model assembly line balancing problem (MMALBP) is an NP-hard problem whichrequires an effective algorithm for solution. 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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Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals by Homayouni, Seyed Mahdi

“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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Cubature kalman optimizer : A novel metaheuristic algorithm for solving numerical optimization problems by Zulkifli, Musa, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai, Tsuboi, Yusei

“…The proposed CKO is validated on CEC 2014 test suite on 30 benchmark functions. To further validate the performance, the proposed CKO is compared with well-known algorithms, including single-agent finite impulse response optimizer (SAFIRO), single-solution simulated Kalman filter (ssSKF), simulated Kalman filter (SKF), asynchronous simulated Kalman filter (ASKF), particle swarm optimization algorithm (PSO), genetic algorithm (GA), grey wolf optimization algorithm (GWO), and black hole algorithm (BH). …”
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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems by Mohd Zakimi, Zakaria, Hishamuddin, Jamaluddin, Robiah, Ahmad, Sayed Mohammad Reza, Loghmanian

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Dynamic obstacle handling in multi-robot coverage by Tay, Wing Le

“…The impacts of the modified algorithm’s parameters on simulation results were also studied to determine the optimal parameters for achieving better performance. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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A discrete event simulation framework for utility accrual scheduling algorithm in uniprocessor environment by Ahmad, Idawaty, K. Subramaniam, Shamala, Othman, Mohamed, Ahmad Zukarnain, Zuriati

“…GUS is one of the existing TUF/UA scheduling algorithms that consider the Time/Utility Function (TUF) of the executed tasks in its scheduling decision. …”
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Performance evaluation of task scheduling using hybrid meta-heuristic in heterogeneous cloud environment by Mohammed, Faten Ameen Saif, Derahman, Mohd Noor, Alwan, Ali Amer, Latip, Rohaya

“…The simulation results prove that the proposed algorithm (GA-DE) outperforms the other existing algorithms in all cases in terms of make-span.…”
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Performance evaluation of task scheduling using hybrid meta-heuristic in heterogeneous cloud environment by A. Saif, Faten, Derahman, Mohd Noor, Alwan, Ali Amer, Latip, Rohaya

“…The simulation results prove that the proposed algorithm (GA-DE) outperforms the other existing algorithms in all cases in terms of make-span.…”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

“…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer by Alam, Mohammad Khurshed

“…The main goal of this study is to use a cuttingedge version of recent metaheuristic algorithm, namely Moth-Flame Optimizer (MFO) algorithm for solving the mentioned OPF problems. …”
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HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets by Hasan, Raed Abdulkareem, Mostafa, A. Mohammed, Salih, Zeyad Hussein, M. A., Ameedeen, Tapus, Nicolae, Mohammed, Muamer N.

“…With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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Optimization 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, mixed-model assembly line balanuinfi problem is used to- analyze the performance of four evolutionary algorithms (E'As), namely particle swarm optimization (PSO), simulated annealing (SA), ant colony optimization (ACO) and genetic algorithm (GA). …”
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An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz by Nor Azlina, Ab. Aziz

“…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

“…Integrating RES into the optimal power flow problem is framed as a multi-objective optimization task. …”