Optimal multiobjective design of robust power system stabilizers using genetic algorithms by Abdel-Magid, Y.L.

“…Optimal multiobjective design of robust multimachine power system stabilizers (PSSs) using genetic algorithms is presented in this paper. …”
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Robust Coordinated Design of Excitation and TCSC-Based Stabilizers Using genetic algorithms by Abdel-Magid, Y. L.

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Learning continuous functions using decision tree learning algorithms by Ibrahim, Ahmed Esmat Mahmoud

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Simultaneous stabilization of multimachine power systems viagenetic algorithms by Abdel-Magid, Y.L.

“…This paper demonstrates the use of genetic algorithms for the simultaneous stabilization of multimachine power systems over a wide range of operating conditions via single-setting power system stabilizers. …”
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Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems by Abdel Magid, Y.L.

“…This paper demonstrates the use of genetic algorithms to design a single output feedback control law for the simultaneous eigenvalue placement of a power system running over a wide range of operating conditions. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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New enumeration algorithm for regular boolean functions by Nasrallah, Walid F.

“…This algorithm exploits the equivalence between regular Boolean functions and positive threshold functions that can be used to represent instances of the knapsack problem. …”
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A new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…The problem under consideration includes two linked subproblems: a combinatorial optimization problem and a nonlinear programming problem. The former is solved using the proposed genetic algorithm while the latter problem is solved via a quadratic programming routine. …”
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A New Penalty Function Algorithm For Convex Quadratic Programming by Bendaya, M.

“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

“…The algorithm is tested using 200 randomly generated 2-variable 4-valued functions. …”
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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Mujahid, S.N.

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

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Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller by Sk. A., Shezan

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Spherical cavity-expansion forcing function in PRONTO 3D for application to penetration problems by Tabbara, Mazen R.

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Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

“…The core of the proposed algorithm is based on genetic algorithms. Tabu search is used to generate new population members in the reproduction phase of the genetic algorithm. …”
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Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems by Abualigah, Laith

“…In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. …”
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Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem by Montawy, A.H.

“…The core of the proposed algorithm is based on genetic algorithms. Tabu search is used to generate new population members in the reproduction phase of the genetic algorithm. …”
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A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem by Mantawy, A. H.

“…This paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. …”
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Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

“…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. …”

Attacking ElGamal based cryptographic algorithms using Pollard's rho algorithm by El-Kassar, A. N.

“…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Pollard's rho algorithm that works in the domain of natural integers. …”
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