Search Results - (( variable generation through algorithm ) OR ( java application optimization algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Article -
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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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 -
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Article -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Thesis -
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Thesis -
13
Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means
Published 2020“…Membership functions are used to depict the fuzzy values of given variable. Though membership functions are determined through expert's opinion, however, the one estimated through heuristic algorithms is the preferable methods. …”
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14
Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation
Published 2018“…We detail the design of this combined algorithm and evaluate it through experiments on multiple synthetic and benchmark problems. …”
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Book Chapter -
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Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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Thesis -
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Optimal Long-Term Hydro Generation Scheduling of Small Hydropower Plant (SHP) using Metaheuristic Algorithm in Himreen Lake Dam
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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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Thesis -
20
Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance
Published 2021“…Finally, mathematical experimentation is proceeded concerning on verification and validation of the new algorithm. The verification performed through generated random problems via MATLAB has shown the new augmentation algorithm maintains to generate a lesser iteration number from the highest percentage of nonzero coefficients in constraints matrix (80%) and the biggest problem sizes (m = 100, n = 100) until to the lowest percentage of nonzero coefficients in constraints matrix (20%) and the smallest problem sizes (m = 5, n = 5). …”
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