Search Results - (( simulation optimization capacity algorithm ) OR ( java application scheduling algorithm ))
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1
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of 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 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 -
2
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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 -
4
Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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Conference or Workshop Item -
5
A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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Final Year Project -
6
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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Thesis -
7
Improving Class Timetabling using Genetic Algorithm
Published 2006“…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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Thesis -
8
Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Thesis -
9
Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Thesis -
10
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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Article -
11
The performance of block codes in digital communication system: article / Nor Afzan Azmi
Published 2007“…This proposed algorithm was developed and simulated to evaluate the performance of handover procedure in order to minimize an unnecessary handover, enhance the system capacity and improve the user's QoS level in the femtocell networks. …”
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Article -
12
Handover procedure between macrocell and femtocell in Long Term Evolution (LTE) network: article / Nurul Afzan Zakaria
Published 2013“…This proposed algorithm was developed and simulated to evaluate the performance of handover procedure in order to minimize an unnecessary handover, enhance the system capacity and improve the user's QoS level in the femtocell networks. …”
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Article -
13
Handover procedure between macrocell and femtocell in long term evolution (LTE) network / Nurul Afzan Zakaria
Published 2013“…This proposed algorithm was developed and simulated to evaluate the performance of handover procedure in order to minimize an unnecessary handover, enhance the system capacity and improve the user's QoS level in the femtocell networks. …”
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Thesis -
14
Batch mode heuristic approaches for efficient task scheduling in grid computing system
Published 2016“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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Thesis -
15
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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17
Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios
Published 2025“…Optimization methods vary depending on objectives, reservoir type, and algorithms used. …”
Article -
18
Performance analysis of resource allocation downlink for MIMO-OFDMA system using Greedy algorithm. / Azrinawati Samaon
Published 2014“…Simulation results show that the proposed algorithm can improve the capacity of the network compared with the waterfdling when using signal-to-noise ratio (SNR) with value 6dB. …”
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Article -
19
Performance analysis of resource allocation downlink for MIMO-OFDMA system using greedy algorithm / Azrinawati Samaon
Published 2016“…Simulation results show that the proposed algorithm can improve the capacity of the network compared with the water-filling when using signal-to-noise ratio (SNR) with value 6dB. …”
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Thesis -
20
Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm
Published 2025“…The simulation reveals that the suggested IPOA algorithm exhibited the most economical performance and the lowest CO2 emissions. …”
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