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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. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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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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A genetic algorithm for capital budgeting problem with fuzzy parameters
Published 2010“…Thereupon, a fuzzy simulation-based genetic algorithm is provided for solving chance constrained integer programming model with fuzzy parameters.…”
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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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Explicit solution of parameter estimate using multiparametric programming for boost converter
Published 2023“…A multiparametric programming (MPP) algorithm is fundamental to the suggested methodology, which aims to develop parameters as explicit functions of measurements. …”
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System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)
Published 2022“…This project present a system program algorithm based on Moth Flame Optimization (MFO) algorithm to assign an optimal set of system program to meet the satisfaction of quality of service requirements of cloud computing in such a way that the total execution time of tasks is minimized. …”
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Academic Exercise -
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Control algorithm for two-tank system using multiparametric programming
Published 2023“…The two-tank system consists of two connected tanks, where the goal is to control the liquid levels in both tanks by manipulating the inflow rates. This study proposes a control algorithm for a two-tank system based on multiparametric programming. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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Thesis -
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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OPTIMAL DESIGN OF A BLDC MOTOR BY GENETIC ALGORITHM
Published 2007“…The project report describes an optimal design of Brushless DC (BLDC) motor using Genetic Algorithm (GA) and Simulated Annealing (SA). A constrained optimization on the objective function is performed and optimal parameters are derived. …”
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Final Year Project -
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Self-similar network traffic using Random Midpoint Displacement (RMD) algorithm / Jumaliah Saarini
Published 2006“…That program we need the sequence of the random number as a data. …”
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Controller And Circuitry Design And Implementation For Fire Fighting Robot For MIROC 2014 Competition
Published 2014“…This algorithm is designed using an iterative design model, whereby the program is continually tested and improved. …”
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Final Year Project -
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Parameter estimation of multivariable system using Fuzzy State Space Algorithm / Razidah Ismail … [et al.]
Published 2011“…In order to enhance the implementation of the algorithm, it is necesssary to develop an efficient computation program together with the user's interface. …”
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Research Reports -
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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