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1
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…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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2
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…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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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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4
Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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5
Pembangunan model pengoptimman pengeluaran minyak sawit dan isirong sawit menggunakan pendekatan genetik kabur
Published 2008“…The developed model is an integration between fuzzy expert system models and multi objective programming model. …”
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Operator Training Simulator Using Plantwide Control for Biodiesel Production from Waste Cooking Oil
Published 2015“…Subsequently, both the processes are optimized considering profit, heat duty and organic waste as objectives, and using an Excel-based multi-objective optimization (EMOO) program for the elitist non-dominated sorting genetic algorithm (NSGA-II). …”
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7
High Pressure Co2 Separation Using Membranes Membrane Selection and Process Modeling
Published 2015“…The optimization for membrane selection was achieved using a multi-objective optimization method while that of module operating conditions was achieved using non-linear programming constraint optimization model and a Golden search algorithm which was implemented using MATLAB. …”
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