Search Results - (( development practical solutions algorithm ) OR ( java simulation optimization algorithm ))
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1
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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2
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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3
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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4
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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6
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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7
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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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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9
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…In this way, the real solution is closely approximated. Through the practical examples, the applicability, efficiency and effectiveness of these integrated sub-algorithms have been demonstrated through solving several practical real world examples. …”
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10
CSC126 - Fundamentals of Algorithms and Computer Problem Solving / Faculty of Computer And Mathematical Sciences
Published 2023“…In the end they are expected to develop the ability to analyze simple problems, organize effective algorithmic solutions for the problems and write computer programs to solve them.…”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
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12
SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity
Published 2019“…Moreover, with the fast development in computing technology, application of optimization algorithm in solving problems is easier and becomes more practical. …”
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14
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Genetic Algorithm (GA), Ant Colony (AC), Simulated Annealling (SA), Particle Swarm Optimization, and Harmony Search Algorithm (HS) as their basis in an effort to generate the most optimal solution. …”
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15
A Hybrid ant colony optimization algorithm for solving a highly constrained nurse rostering problem
Published 2019“…Specifically, three main phases were involved in developing the hybrid model, which are generating an initial roster, updating the roster through the ACO algorithm, and implementing the hill climbing to further search for a refined solution. …”
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16
Agreement options for negotiation on material location decision of housing development
Published 2020“…Decision algorithms are based on the cooperative game theory to develop the agreement options and coalition formation. …”
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The Anglerfish algorithm: a derivation of randomized incremental construction technique for solving the traveling salesman problem
Published 2019“…Smart algorithms have been developed to address this issue. …”
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Genetic Algorithm for Forecasting Bioinformatic Outcomes of Mutation-induced Cowpeas for Sustainable Development
Published 2023“…The study applied genetic algorithm as a stochastic optimizer using Python programming to determine the convergence pattern for obtaining an optimal cowpea solution that combines high yield and drought-tolerance. …”
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SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing
Published 2019“…To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. SecPath is evaluated with several variations using 400 nodes in WSN deployments as well as large-scale simulations. …”
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20
Alternative method for economic dispatch utilizing grey wolf optimizer
Published 2015“…Although several optimization methodologies have been developed for solving ED problems, the complexity of the task reveals the necessity for development of efficient algorithms to accurately locate the optimum solution. …”
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