Scalable parallel algorithms for difficult combinatorial problems by Abu-Khzam, Faisal N.

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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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Optimization metaheuristic for software testing by Mansour, Nashat

“…We formulate the web application 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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Investigating the Impact of Skylights and Atrium Configurations on Visual Comfort and Daylight Performance in Dubai Shopping Malls by SANAD, AYMAN ADEL AHMED

“…Annual simulations are used to assess seasonal variations, while sensitivity analysis identifies key parameters. A genetic algorithm and multi-objective optimisation (MOO) simulations are used to generate optimal configurations, summarised in the form of a Pareto front selection criteria guide the choice of the optimum solution, which is then applied and analysed in a case study. …”
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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 VLSI cell placement by Sait, Sadiq M.

“…This approach can be followed by other iterative (meta-) heuristics to find desirable solutions to optimization problems with noisy search space and possibly more than one objective. …”
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Computational Experience On Four Algorithms For The Hard Clustering Problem by AlSultan, K.S.

“…In this paper, we consider the problem of clustering m objects in c clusters. The objects are represented by points in n-dimensional Euclidean space, and the objective is to classify these m points into c clusters such that the distance between points within a cluster and its center is minimized. …”
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Fuzzy simulated evolution algorithm for topology design of campusnetworks by Youssef, H.

“…This choice is dictated by physical and technological constraints and must optimize several objectives. Example of objectives are monetary cost, network delay, and hop count between communicating pairs. …”
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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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Online Control and Optimization of Directional Drilling by unknown

“…Gravitational Search Algorithm (GSA) is developed to search for optimal settings of the proposed controller. …”
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Graph contraction for physical optimization methods by Mansour, Nashat

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Distributed dimension reduction algorithms for widely dispersed data by Abu-Khzam, F.N.

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Simulated evolution algorithm for multiobjective VLSI netlist bi-partitioning by Sait, Sadiq M.

“…In this paper the Simulated Evolution algorithm (SimE) is engineered to solve the optimization problem of multi-objective VLSI netlist bi-partitioning. …”
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Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems by Abdel Magid, Y.L.

“…The task of selecting the output feedback gains is converted to a simple optimization problem with an eigenvaluebased objective function, which is solved by a genetic algorithm. …”
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A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS by Youssef, H.

“…This choice is dictated by physical and technological constraints and must optimize several objectives. Important objectives are monetary cost, network delay, hop count between communicating pairs, and reliability. …”
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A family of minimum curvature variable-methods for unconstrained optimization. (c1998) by Obeid, Samir Y.

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Environmental/economic power dispatch using multiobjective evolutionary algorithms by Abido, M.A.

“…The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new strength Pareto evolutionary algorithm (SPEA) based approach is proposed to handle the EED as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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Evolutionary Game-Based Battery Scheduling: A Comparative Study for Prosumers in Smart Grids by Anas Karaki (17947808)

“…The primary objective is to develop an efficient, reliable, private, and scalable algorithm for battery scheduling that ensures economic efficiency and system stability, even under dynamic market conditions. …”

Optimizing Aircraft Pitch Control Systems: A Novel Approach Integrating Artificial Rabbits Optimizer with PID-F Controller by Abualigah, Laith

“…The study employs a time-domain-based objective function to guide the optimization process. …”
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A simulated annealing algorithm for the capacitated vehicle routing problem by Azar, Danielle

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