A Tabu Search algorithm for mapping data to multicomputers. (c1997) by Diab, Kamal M.

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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data by Behrouz Ahadzadeh (19757022)

“…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”

Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”

Improved search-tree algorithms for the cluster edit problem. (c2011) by Ghrayeb, Ali Kassem

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Stochastic Search Algorithms for Exam Scheduling by Mansour, Nashat

“…In this work, we use a modified weighted-graph coloring problem formulation and adapt two stochastic search algorithms for solving the problem. The two algorithms are a simulated annealing algorithm (SA) and a genetic algorithm (GA). …”
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Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

“…In this paper, we present a Scatter Search (SS) algorithm for predicting 3D structures of proteins based on torsion angles representation. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015) by Wehbe, Gioia Wahib

“…Then, it searches for population discriminative motifs or differentiable sequence of SNPs, by implementing Probabilistic Suffix Trees data structures. …”
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A decentralized load balancing strategy for parallel search-three optimization. (c2010) by Mouawad, Amer E.

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A parallel search tree algorithm for vertex cover on graphical processing units. (c2013) by Kabbara, Rashad Karim

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A Scatter search algorithm for exam scheduling. (c2006) by Isahakian, Vatche Raffi

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Upgraded SemIndex Prototype Supporting Intelligent Database Keyword Queries through Disambiguation, Query as You Type, and Parallel Search Algorithms by Tekli, Joe

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The buffered work-pool approach for search-tree based optimization algorithms by Abu-Khzam, Faisal N.

“…This new trend has been motivated by hardness of approximation results that appeared in the last decade, and has taken a great boost by the emergence of parameterized complexity theory. Exact algorithms often follow the classical search-tree based recursive backtracking strategy. …”
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Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem by Denis Alicic (23073484)

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Scatter search for protein structure prediction. (c2008) by Kehyayan, Christine Houry

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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)

“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”

Teaching–learning-based optimization algorithm: analysis study and its application by Abualigah, Laith

“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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A fast exact sequential algorithm for the partial digest problem by Mostafa M. Abbas (17058093)

“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”

Design and implementation of a deep learning-empowered m-Health application by Akhan Akbulut (17380285)