Search Results - (( simulation optimization task algorithm ) OR ( solution using based algorithm ))

Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators by Abed I.A., Sahari K.S.M., Koh S.P., Tiong S.K., Jagadeesh P.

“…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”

Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Furthermore, it enables non-dominated evaluation of solutions based on four objectives using crowding distance for selection. …”
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Hybrid Henry Gas-Harris Hawks comprehensive-opposition algorithm for task scheduling in cloud computing by Omran Alkaam, Nora, Md Sultan, Abu Bakar, Hussin, Masnida, Yatim Sharif, Khaironi

“…By optimizing task scheduling, cloud computing solutions can decrease processing times, boost efficiency, and improve overall system performance. …”
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Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment by Gabi, Danlami, Ismail, Abdul Samad, Zainal, Anazida, Zakaria, Zalmiyah, Al-Khasawneh, Ahmad

“…In this study, a Cloud Scalable Multi-Objective Cat Swarm Optimization-based Simulated Annealing algorithm is proposed. …”
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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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Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling by Homayouni, Seyed Mahdi, Tang, Sai Hong, Ismail, Napsiah, Mohd Ariffin, Mohd Khairol Anuar

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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Meta-heuristic algorithms have widely used in HPAs due to their global optimization ability. …”
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem by Ibrahim Abaker , Targio Hashem

“…The proposed algorithm is evaluated using tasks scheduling in the scheduling load simulator and validated using statistical modeling. …”
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An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization by Majid, Mad Helmi Ab.

“…To adaptively switches between the two algorithms, an adaptive switching algorithm based on a Generalized Likelihood Ratio Test (GLRT) is proposed. …”
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Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm by Abed I.A., Koh S.P., Sahari K.S.M., Jagadeesh P., Tiong S.K.

“…A method based on a modified electromagnetism-like with two-direction local search algorithm (MEMTDLS) and genetic algorithm (GA) is proposed to determine the optimal time of task scheduling for dual-robot manipulators. …”

Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…In this work, three new estimation-based metaheuristic algorithms are introduced. The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…In this work, three new estimation-based metaheuristic algorithms are introduced. The first algorithm is a single-agent-based algorithm, named Single-agent FIR optimizer (SAFIRO). …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

“…Training neural networks particularly back propagation algorithm is a complex task of great importance in the field of supervised learning. …”
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Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system by Khaksar, Weria, Tang, Sai Hong, Mohamed Sahari, Khairul Salleh, Khaksar, Mansoor, Toressen, Jim

“…Despite the proven advantages of sampling-based motion planning algorithms, their inability to handle online navigation tasks and providing low-cost solutions make them less efficient in practice. …”
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Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm by Kasim Hawari, Mohd Zarifitri

“…Finally, the simulation was conducted by implementing a random algorithm to verify the proposed GA in terms of the mobile robot's minimum and maximum path lengths. …”
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Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system by Khaksar W., Hong T.S., Sahari K.S.M., Khaksar M., Torresen J.

Independent task scheduling algorithms in fog environments from users’ and service providers’ perspectives: a systematic review by Al-Qadhi, Abdulrahman K., Latip, Rohaya, Chiong, Raymond, Athauda, Rukshan, Hussin, Masnida

“…To address these issues, a substantial amount of work has been done to determine optimal methods to improve QoS using task scheduling algorithms. …”
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Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm by Arezoumand, Reza

“…Developing an exploration algorithm based on spanning tree is the main contribution. …”
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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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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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