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101
Evolutionary algorithms for VLSI multi-objective netlist partitioning
Published 2006“…In this paper, we engineer three iterative heuristics for the optimization of VLSI netlist bi-partitioning. These heuristics are based on Genetic Algorithms (GAs), Tabu Search (TS) and Simulated Evolution (SimE). …”
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102
Computational Experience On Four Algorithms For The Hard Clustering Problem
Published 2020“…Several algorithms have been developed to solve this problem which include the k-means algorithm, the simulated annealing algorithm, the tabu search algorithm, and the genetic algorithm. …”
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103
An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive
Published 2006“…At each operating condition a genetic algorithm (GA) is used to optimize proportional-integral (PI) controller parameters in a closed loop vector control scheme. …”
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104
An evolutionary algorithm for solving the geometrically constrained site layout problem
Published 2017“…The proposed algorithm is two-phases: an initialization phase that generates an initial population of layouts through a sequence of mutation operations, and a reproduction phase that evolve the layouts generated in phase one through a sequence of genetic operations aiming at finding an optimal layout. …”
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105
Evolutionary algorithms, simulated annealing and tabu search: a comparative study
Published 2020“…All rights reserved. Keywords: Genetic algorithms; Simulated annealing; Tabu search; Fuzzy logic; Floorplanning; Combinatorial optimization; VLSI…”
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106
A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch
Published 2001“…A new nondominated sorting genetic algorithm (NSGA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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107
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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108
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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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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111
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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Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
Published 2003“…A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. …”
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114
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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115
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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116
Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
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doctoralThesis -
117
On-site workshop investment problem: A novel mathematical approach and solution procedure
Published 2023“…Next, due to the NP-hardness of the problem, an enhanced Genetic Algorithm (GA)-based metaheuristic with efficient problem-specific improvement rules as local search and effective crossover and mutation operators is proposed. …”
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118
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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