Search Results - (( java simulation optimization algorithm ) OR ( programming point effect algorithm ))
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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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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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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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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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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
An alternative method to solve combined economic emission dispatch problems using flower pollination algorithm
Published 2016“…The proposed algorithm are tested on four different test systems which are: 6-generating unit and 11-generating unit without valve point effect with no transmission loss, 10-generating unit with having valve point effect and transmission loss, and lastly 40-generating unit with having valve point effect without transmission loss. …”
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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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9
Comparison Between Linear Programming And Integer Linear Programming: A Review
Published 2018“…Two techniques to solve LP, simplex method and interior-point method were introduced. For ILP, available algorithms can be classified into exact algorithms and heuristic algorithms. …”
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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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11
Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…Researchers from the Satellite Navigation Research Group (SNAG) of UTM are currently conducting a research program that mitigates the effect of the Anti-Spoofing (AS) policy. …”
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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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Solving non-convex economic dispatch problem using computational intelligence technique
Published 2023“…Computer programming; Immune system; Scheduling; Artificial Immune System; Computational intelligence techniques; Economic Dispatch; Evolutionary programming algorithms; Log-normal; Non-convex economic dispatches; Reliability test system; Valve-point loading effect; Electric load dispatching…”
Conference Paper -
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An efficacious multi-objective fuzzy linear programming approach for optimal power flow considering distributed generation
Published 2016“…An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. …”
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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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16
Designing and implementation of robot mapping algorithm for mobile robot
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An improved adaptive shuffled frog leaping algorithm to solve various non smooth economic dispatch problems in power system / Mohamad Helmi Muhamad Izham
Published 2016“…The proposed IASFLA method is developed using MATLAB programming. The IASFLA method is tested on a ten generator units system with valve-point loading effects and multifuel source options. …”
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Energy efficient path reconstruction in wireless sensor network using iPath
Published 2019“…To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. Energy efficient iPath (E-iPath) is evaluated with several variations of nodes in WSN deployments as well as large-scale simulations. …”
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Development of adaptive controlled natural gas transmission water bath heater using mathematical model / Amiruddin Amkaromi
Published 2018“…Due to this limitation, the adaptive set point regulation algorithm was formulated. The set point adjustment mechanism adjusted the set point input by adding up the error between model response and actual response so that during undershoot (less than set point), the control output will be augmented while during overshoot (more than set point), the control output will be diminished. …”
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