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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem
Published 2018“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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83
Minimum UAV fog servers with maximum IoT devices association using genetic algorithms
Published 2021“…We then propose a heuristic sub-optimal approach based on genetic algorithm (GA) to decide on the minimum number of UAVs to be deployed and the IoT-to-UAV association. …”
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conferenceObject -
84
Using artificial bee colony to optimize software quality estimation models. (c2015)
Published 2016“…We compare our models to others constructed using other well established techniques such as C4.5, Genetic Algorithms, Simulated Annealing, Tabu Search, multi-layer perceptron with back-propagation, multi-layer perceptron hybridized with ABC and the majority classifier. …”
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masterThesis -
85
Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog...
Published 2023“…This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. The calibrated simulation model based on indoor and outdoor measured temperature for a school of interest is used to evaluate the optimization strategies. …”
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86
Power-constrained system-on-a-chip test scheduling using a genetic algorithm
Published 2006“…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. The method minimizes the overall test application time of a system-on-a-chip through efficient and compact test schedules. …”
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87
Performance Assessment of Foraging Algorithms vs. Evolutionary Algorithms
Published 2012“…This work provides a complete performance assessment of the four mentioned algorithms in comparison to the widely known differential evolution (DE), genetic algorithms (GAs), harmony search (HS), and particle swarm optimization (PSO) algorithms when applied to the problem of unconstrained nonlinear continuous function optimization. …”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
Published 2021“…Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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91
Parametric Design Optimization in Sustainable Urban Design: In Hot Climate
Published 2012“…This research employs Genetic algorithms as the computational design methodology to achieve parametric design optimization to design for a more sustainable cities and urban. …”
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Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
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doctoralThesis -
94
A Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System
Published 2021“…In the first phase, a genetic algorithm (GA) with a variable population size is used to update the deployment of SPs. …”
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Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks
Published 2021“…We implement a simulation environment to benchmark the proposed distributed DRL-based method against other methods such as Q-Learning (QL) and Deep Q-Networks (DQN), and centralized heuristic power allocation algorithms. Our simulation results show that the distributed DDPG-based algorithm learns to adapt against changes in the channel or user requirements, while centralized Genetic Algorithm and Particle Swarm Optimization-based algorithms fail to endure against these changes even with coordination between APs. …”
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Fuzzy simulated evolution for power and performance optimization ofVLSI placement
Published 2001“…This is a hard multiobjective combinatorial optimization problem with no known exact and efficient algorithm that can guarantee finding a solution of specific or desirable quality. …”
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Energy removal in dynamical systems through an optimal sequence of constraint application
Published 2017“…The optimization process is illustrated by means of simple mass-spring and membrane systems and the corresponding problems are solved using a genetic algorithm.…”
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98
A hybrid model for the optimum integration of renewable technologies in power generation systems
Published 2011“…The main purpose of this work is to assess the unavoidable increase in the cost of electricity of a generation system by the integration of the necessary renewable energy sources for power generation (RES-E) technologies in order for the European Union Member States to achieve their national RES energy target. The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. …”
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A method for optimizing test bus assignment and sizing for system-on-a-chip
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