A Novel Centrality-Based Approach for Link Prediction by El Khoury, Elissa Lichaa

“…Namely, we consider weighted betweenness, closeness and Katz centralities, in addition to the Resource Allocation and Adamic-Adar indices. We also use a genetic algorithm to optimize the weights of these metrics, reflecting their contributions to link prediction. …”
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Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

“…In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …”
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Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives by Nasir Uddin, M.

“…At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. …”
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Complexity Avoidance using Biological Resemblance of Modular Multivariable Structure by Kouatli, Issam

“…GFT (Genetic Fuzzimetric Technique) is of no exception which merges Fuzzy logic with genetic algorithm to achieve the optimization of the decision making process under uncertainty. …”
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Simulated evolution for timing and low power VLSI standard cell placement by Sait, Sadiq M.

“…For this hard multiobjective combinatorial optimization problem, no known exact and efficient algorithms exist that guarantee finding a solution of specific or desirable quality. …”
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Data Generation for Path Testing by Mansour, Nashat

“…The two algorithms are: a simulated annealing algorithm (SA), and a genetic algorithm (GA). …”
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Dynamic single node failure recovery in distributed storage systems by Itani, M.

“…To minimize the system repair cost, we formulate our problem using incidence matrices and solve it heuristically using genetic algorithms for all possible cases of single node failures. …”
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Final exams scheduling for univeristies. (c2001) by Timany, Mazen Nuhad

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Joint Planning of Smart EV Charging Stations and DGs in Eco-Friendly Remote Hybrid Microgrids by Shaaban, Mostafa

“…The planning problem jointly allocates and sizes a set of distributed generators (DGs) along with the EV charging stations to balance the supply with the total demand of regular loads and EV charging. The planning algorithm specifies optimal locations and sizes of the EV charging stations and DG units that minimize two conflicting objectives: (a) deployment and operation costs and (b) associated green house gas emissions, while satisfying the microgrid technical constraints. …”
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Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle by Korkmaz, Jessica

“…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …”
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Iterative heuristics for multiobjective VLSI standard cellplacement by Sait, Sadiq M.

“…We employ two iterative heuristics for the optimization of VLSI standard cell placement. These heuristics are based on genetic algorithms (GA) and tabu search (TS) respectively. …”
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Tuning of AGC of interconnected reheat thermal systems with geneticalgorithms by Abdel-Magid, Y.L.

“…This paper deals with the application of genetic algorithms for optimizing the automatic generation control (AGC) systems. …”
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EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING by Sait, Sadiq M.

“…These heuristics are based on Genetic Algorithms (GAs) and Tabu Search (TS) [sadiq et al., 1999] respectively. …”
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A novel network-based SIS framework for improved GA performance by Tohme, Rawane

“…Genetic algorithms have long been used to solve complex optimization problems by mimicking natural selection processes. …”
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Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

“…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

“…Numerical experiments on synthetic and real-life data demonstrate the effectiveness of the proposed method. The NES algorithm achieves perfect precision on the synthetic data and near optimal accuracy on the real-life data. …”
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Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves by S. Andhale, Yogesh

“…The genetic optimization (GO) method is used to further refine the location of damage within the enclosed area obtained using astroid algorithm. …”
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Enhancement of Frequency Control for Stand-Alone Multi-Microgrids by Kavita Singh (182141)

“…For getting superior outcomes and enhanced steadiness of the microgrid, the controller gains are streamlined utilizing an imperialist competitive algorithm (ICA). To demonstrate the efficiency of ICA, The obtained results are compared with the genetic algorithm and particle swarm optimization algorithm. …”

Parallel processing by Mansour, Nashat

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Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management by Islam Eljilany (14151588)

“…As per 10.3% prevalence of genetic variants, 82% bridging, and a calculated 20% optimization in the preparative period of warfarin management, the benefit to cost ratio was 4.0 in favor genotype-guided approach. …”