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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism. …”
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Monograph -
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Thesis -
3
Resource management in grid computing using ant colony optimization
Published 2011“…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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Monograph -
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Article -
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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A New Approach To The Solution Of Economic Dispatch Using Genetic Algorithm
Published 2016“…The main idea of this paper focuses on the application of genetic algorithm in order to identify the best solution to an economic dispatch problem by using a new approach depending on Bmn coefficients and arithmetic crossover of the genetic algorithm. …”
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Article -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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16
Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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17
Loss reduction in distribution networks using new network reconfiguration algorithm
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem
Published 2008“…Results show that these new sequential and parallel algorithms run faster than the standard sequential and parallel FDTD algorithms. …”
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20
Enhancement of Ant System Algorithm for Course Timetabling Problem
Published 2009“…Results of the experiments that were conducted using various data sets showed that the proposed algorithm produced better course schedule solution than the Greedy Algorithm, Genetic Algorithm, and other variants of Ant System Algorithm.…”
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