Search Results - (( development through optimisation algorithm ) OR ( java loading optimization algorithm ))

Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

“…The superior performances of the developed bats echolocation-inspired algorithms are verified through rigorous tests with optimisation benchmark test functions and problems. …”
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Improved Bat Algorithm for faster convergence in solving optimisation problem by Ramli, Mohamad Raziff

“…For comparison, three established algorithms namely Harmony Search (HS), Particle Swarm Optimisation (PSO) and Genetic Algorithm (GA) are analysed through the same set of experiments and compared with the IBA. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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Chaotic Immune Symbiotic Organisms Search algorithm for solving optimisation problem by Zamani M.K.M., Musirin I., Suliman S.I., Mustaffa S.A.S.

“…Good performance of these heuristics-based algorithm has been implied through various implementation in solving optimisation problems. …”

Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

“…This thesis focuses on the development of a new stream of crossover within genetic algorithms, called Optimised Crossover Genetic Algorithm (OCGA) for solving combinatorial optimisation problems, which takes into account the objective function in finding the best ofspring solution among an exponentially large number of potential ofspring. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…In conclusion, a deep reinforcement learning algorithm was successfully developed for the substrate feeding rate optimisation in the fed-batch baker’s yeast fermentation process. …”
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Strategies for effective value management practice in construction industry by Zulhkiple, A. Bakar

“…This dissertation explores the development of VM methodology through the joint use of a finite element software (Etabs) and genetic algorithm (GA) optimisation design to minimise the cost value of buildings by optimising structural elements. …”
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Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Gait identification and optimisation for amphi-underwater robot by using ant colony algorithm by Mohd Yusof, Muhammad Syafiq, Toha @ Tohara, Siti Fauziah

“…For the optimization, the robot will travel from one specific point to another with the predefined position within optimized gait and fastest time by using Ant Colony Optimization (ACO) technique. The algorithm being compared, between Ant Colony Algorithm (ACO) and the Particle Swarm Optimisation (PSO) in terms of time and distance. …”
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Breast cancer diagnosis through an optimization-driven multispectral gamma correction (ODMGC) by Raj A, Arul Edwin, Ahmad, Nabihah, Durai S, Ananiah

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A Hybrid Metaheuristic Technique Based on Grey Wolf Optimisation, Symbiotic Organism Search, and Ant Colony Optimisation for Solving Multi-Objective Vehicle Routing Problems by Ary, Maxsi

“…Beyond its application in the Boyolali case, validation through benchmark datasets and various optimisation strategies confirms that HMGSA can be applied to other logistics routing scenarios across different operational contexts. …”
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Optimal algorithms for the charge equalisation controller of series connected lithium-ion battery cells in electric vehicle applications by Hoque M.M., Hannan M.A., Mohamed A.

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Linking of these platforms are through a five-step process – monitoring, recording, processing, optimising, and reporting. …”
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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm by Jamal S., Pasupuleti J., Rahmat N.A., Tan N.M.L.

“…In order to demonstrate the effectiveness of the proposed algorithm, The outcomes of the simulation are juxtaposed with results obtained from the initial Pelican Optimisation Algorithm (POA), the Bat Algorithm, and the Improved Differential Evolutionary (IDE) Algorithm. …”

Modelling and optimisation of cooling-slope parameters of magnesium AZ91D using improvement multi-objective Jaya approach for predicted feedstock performance by Mohd Said, Rahaini, Salleh@Sallehuddin, Roselina, Mohamed Radzi, Norhaizan, Wan Ali, Wan Fahmin Faiz, Mohamad Kamal, Mohamad Ridzuan

“…Then, mathematical regression models were developed from the data obtained and implemented as an objective function equation in the MOO optimisation process. …”
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Hybrid particle swarm optimization algorithm with fine tuning operators by Murthy, G.R., Arumugam, M.S., Loo, C.K.

“…The effectiveness of the fine tuning elements with various PSO algorithms is tested through three benchmark functions along with a few recently developed state-of-the-art methods and the results are compared with those obtained without the fine tuning elements. …”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

“…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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