Incremental & classical genetic algorithm. (c2001) by Awad, Mohamad M.

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A SIMULATED ANNEALING ALGORITHM FOR THE CLUSTERING PROBLEM by Selim, S.Z.

“…In this paper we discuss the solution of the clustering problem usually solved by the K-means algorithm. The problem is known to have local minimum solutions which are usually what the K-means algorithm obtains. …”
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A simulated annealing algorithm for unit commitment by Mantawy, A.H.

“…This paper presents a simulated annealing algorithm (SAA) to solve the unit commitment problem (UCP). …”
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A new multimodulus blind equalization algorithm by Abrar, Shafayat

“…The phase-recovery and intersymbol interference optimization properties, exhibited by the proposed algorithm, are also discussed.…”
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Adaptive bias simulated evolution algorithm for placement by Youssef, H.

“…Simulated Evolution (SE) is a general meta-heuristic for combinatorial optimization problems. A new solution is evolved from current solution by relocating some of the solution elements. …”
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A New Parallel Genetic Algorithm Model by Al-Somani, Turki F.

“…This paper presents an implementation of three Genetic Algorithm models for solving a reliability optimization problem for a redundancy system with several failure modes, a modification on a parallel a genetic algorithm model and a new parallel genetic algorithm model. …”
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Artificial neural network algorithms. (c1999) by Ramadan, Samer N.

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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm by Abu Zitar, Raed

“…The slime mould algorithm (SMA) gives good results in finding the best solutions to optimization problems. …”
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Hybrid Interval Type-2 Fuzzy PID+I Controller for a Multi-DOF Oilwell Drill-String System by Abdelbaset Laib (16904688)

“…<p>The control of multibody drill-string systems is not easy and designing such systems is considered challenging because of the difficulty in the dynamic analysis of its nonlinear characteristics and parametric uncertainties. An optimal hybrid interval Type-2 fuzzy PID+I logic controller (OH-IT2FPID+I) using a practical swarm optimization algorithm for a multi-degree-of-freedom oil well drill-string system is proposed in this paper. …”

Impact of Charging Electric Vehicles under Different State of Charge Levels and Extreme Conditions by Claude Ziad El-Bayeh (17542284)

“…This paper defines extreme conditions as the state of a load or network that breaks the limits of the constraints in an optimization model. Once these constraints are violated, the optimization algorithm might not work correctly and might not converge to a feasible solution, especially when the complexity of the system increases and includes nonlinearities. …”

Multiobjective Evolutionary Algorithms for Electric Power Dispatch Problem by Abido, M. A.

“…The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) for solving a real-world power system multiobjective nonlinear optimization problem are comprehensively discussed and evaluated in this paper. …”
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Multiobjective evolutionary algorithms for electric power dispatch problem by Abido, M.A.

“…The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) for solving a real-world power system multiobjective nonlinear optimization problem are comprehensively discussed and evaluated in this paper. …”
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Control of nonlinear dynamical systems using genetic algorithms by Al-Duwaish, H.N.

“…This paper introduces a new method for the control of nonlinear systems using genetic algorithms. The proposed method formulates the nonlinear controller design as an optimization problem and genetic algorithms are used in the optimization process. …”
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Capturing outline of fonts using genetic algorithm and splines by Sarfraz, M.

“…We present a method to convert the original problem into a discrete combinatorial optimization problem and solve it by a genetic algorithm. …”
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Inferential sensing techniques in industrial applications by Shakil,, Muhammad

“…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …”
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Computational Experience On Four Algorithms For The Hard Clustering Problem by AlSultan, K.S.

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

“…The problem of selecting the parameters of power system stabilizers which simultaneously stabilize this set of plants is converted to a simple optimization problem which is solved by a genetic algorithm with an eigenvalue-based objective function. …”
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Fuzzy simulated evolution algorithm for topology design of campusnetworks by Youssef, H.

“…The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. …”
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Fuzzy simulated evolution algorithm for VLSI cell placement by Sait, Sadiq M.

“…There has not been a consensus on how to accommodate all these (conflicting) requirements in the search for near optimal feasible solutions. In this paper, we present a fuzzy simulated evolution (FSE) algorithm to tackle this problem. …”
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Timing driven genetic algorithm for standard-cell placement by Sait, Sadiq M.

“…As the algorithm starts converging toward generations with acceptable delay properties, the objective is dynamically adjusted toward optimizing area and routability. …”
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