Search Results - (( simulation optimization task algorithm ) OR ( using location method algorithm ))
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Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators
Published 2023“…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. …”
Conference paper -
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Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm
Published 2023“…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. …”
Article -
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Multi-objective optimization for integrated task scheduling and load balancing in fog computing for IoT applications
Published 2025“…By using a task scheduling and offloading method, the FOCS algorithm arranges data according to size and sends it to the appropriate fog nodes. …”
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Thesis -
4
Scheduling scientific workflow using multiobjective algorithm with fuzzy resource utilization in multi-cloud environment
Published 2020“…Simulation experiments reveal that FR-MOS outperforms the basic MOS over the PSO algorithm.…”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…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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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources
Published 2025“…Integrating RES into the optimal power flow problem is framed as a multi-objective optimization task. …”
Review -
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High impedance fault detection and localization in 11kV distribution system / Mohd Syukri Ali
Published 2018“…Subsequent algorithm simulation results show that the proposed methods are able to detect and subsequently locate the faults with high accuracies. …”
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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Academic Exercise -
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Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application
Published 2024“…Simulation results showed that the proposed ACO algorithm with the modified efficiency factor improved the performance of basic ACO algorithm for solving task allocation problem in terms of the average total travel cost for each agent. …”
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Article -
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OTS: an optimal tasks scheduling algorithm based on QoS in cloud computing network
Published 2019“…This study presents an optimal tasks scheduling algorithm by enhancing Max-Min algorithm. …”
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Task scheduling in cloud computing using Harris-Hawk Optimization
Published 2024“…This paper presents a simulation of the Harris-Hawk Optimization (HHO) algorithm, which aims to minimize the makes pan of a specified task set in a cloud computing environment. …”
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Proceedings -
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An evaluation of network load balancing through Ant Colony Optimization (ACO) based technique / Muhammad Nur Zikri Mohamad Hafizan
Published 2020“…The results also show that the ACO algorithm was able to outperform the Randomized and Round Robin algorithm in all simulation configurations.…”
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Student Project -
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Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment
Published 2018“…In this study, a Cloud Scalable Multi-Objective Cat Swarm Optimization-based Simulated Annealing algorithm is proposed. …”
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An optimal tasks scheduling algorithm based on QoS in cloud computing network
Published 2017“…This study presents an optimal task scheduling algorithm by enhancing Max-Min and TS algorithm. …”
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15
Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…This research explores a new approach of using a multi-objective evolutionary algorithm (MOEA) to evolve robot controllers in performing phototaxis tasks while avoiding obstacles in a simulated 30 physics environment, to overcome problems involving more than one objective, where these objectives usually trade-off among each other and are expressed in different units. …”
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Research Report -
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An enhanced discrete symbiotic organism search algorithm for optimal task scheduling in the cloud
Published 2021“…Therefore, in this paper, we propose a metaheuristic enhanced discrete symbiotic organism search (eDSOS) algorithm for optimal task scheduling in the cloud computing setting. …”
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Multi-objective grey wolf optimizer algorithm for task scheduling in cloud-fog computing
Published 2023“…The simulation result verifies the effectiveness of the MGWO algorithm compared to the state-of-the-art algorithms in reducing delay and Energy consumption.…”
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Enhanced utility accrual scheduling algorithms for adaptive real time system.
Published 2009“…We compared the performances of these algorithms by using discrete event simulation. Results: The proposed PUAS algorithm achieved the highest accrued utility for the entire load range. …”
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A genetic algorithm for optimization of integrated scheduling of cranes, vehicles, and storage platforms at automated container terminals
Published 2014“…Results show that the proposed GA is able to find fairly near optimal solutions similar to the existing simulated annealing algorithm. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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