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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Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

“…We formulate the testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequences of events while keeping the test suite size reasonable. …”
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Artificial neural network algorithms. (c1999) by Ramadan, Samer N.

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Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

“…The results show that our algorithm is able to produce 3D structures with good sub-optimal energy values. …”
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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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Evolutionary algorithms for VLSI multi-objective netlist partitioning by Sait, Sadiq M.

“…Further, we compared the results of the iterative heuristics with a modified FM algorithm, named PowerFM, which targets power optimization. …”
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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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A new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…This paper presents a new genetic algorithm approach to solve the unit commitment problem in electric power systems. …”
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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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Algorithmic Study of Online Multi-Facility Location Problems by Markarian, Christine

“…The latter is a worst-case analysis that compares the cost of the online algorithm to that of the optimal offline algorithm that is assumed to know all demands in advance. …”
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Bridge Structural Health Monitoring Using Mobile Sensor Networks by Amin, Fouad

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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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