Parameter Estimation Of Wiener-Hammerstein Models Via Genetic Algorithms by Emara-Shabaik, Husam

“…In this paper, a modified genetic algorithm is used as a procedure to solve the parameter identification problem of the nonlinear Wiener-Hammerstein models. …”
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A simulated annealing algorithm for the capacitated vehicle routing problem by Azar, Danielle

“…In this paper, we present a meta-heuristic approach for solving the CVRP based on simulated annealing. The algorithm uses a combination of random and deterministic operators that are based on problem knowledge information. …”
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A simulated annealing algorithm for the capacitated vehicle routing problem by Azar, Danielle

“…In this paper, we present a meta-heuristic approach for solving the CVRP based on simulated annealing. The algorithm uses a combination of random and deterministic operators that are based on problem knowledge information. …”
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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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A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…The model takes the uncertainties in the forecasted load demand and the spinning reserve constraints in a fuzzy frame. The genetic algorithm (GA) approach is then used to solve the proposed fuzzy UCP model. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

“…Among these, K-means is widely used for efficiently solving clustering problems. …”
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Fixed-parameter algorithms for hitting set problems. (c2006) by Masri, Rola El.

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Use of Data Mining Techniques to Detect Fraud in Procurement Sector by AL HAMMADI, SUMAYYA ABDULLA

“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) by Moujabber, Bassam N.

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

A new simulated annealing-based tabu search algorithm for unitcommitment by Mantawy, A.H.

“…The algorithm integrates the use of simulated annealing (SA) and tabu search (TS) for solving the UCP. …”
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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem by Abu Zitar, Raed

“…The measurements and track generation are simulated using Stone Soup software. On the other hand, the optimization of the problem is implemented using several evolutionary-based metaheuristic algorithms. …”
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Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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An Efficient Tabu Search Algorithm For The Single-Machine Mean Tardiness Problem by Bendaya, M.

“…In this paper, an efficient tabu search algorithm is prepared ibr solving the singlemachine mean tardiness problem. …”
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Scalable parallel algorithms for dynamic programming on tree decomposition. (c2017) by Yassine, Mohamad M.

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A parallel optimization algorithm for the maximum clique problem. (c2008) by Rizk, Mohamad A.

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A parallel genetic algorithm for the geometrically constrained site layout problem by Zouein, P.

“…This paper presents a parallel genetic algorithm to solve the geometrically constrained site layout problem that involves coordinating the use of limited space to accommodate temporary facilities subject to geometric constraints. …”
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Simulated annealing and improved genetic algorithms for path testing. (c1997) by Joumaa, Rania

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

“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

“…Abstract Evolutionary algorithms, simulated annealing (SA), and tabu search (TS) are general iterative algorithms for combinatorial optimization. …”
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