Stochastic Search Algorithms for Exam Scheduling by Mansour, Nashat

“…Then, we empirically compare the three proposed algorithms and FESP using realistic data. Our experimental results show that SA and GA produce good exam schedules that are better than those of FESP heuristic procedure. …”
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A Scatter search algorithm for exam scheduling. (c2006) by Isahakian, Vatche Raffi

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Three-phase approach for curriculum-based course timetabling problem. (c2012) by Jazzar, Hanaa Salem El-

Subjects: “…Scheduling -- Data processing…”
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Exam scheduling algorithms. (c1999) by Mikati, Ziad

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A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems by Raka Jovanovic (17947838)

“…In this paper, the focus is on the problem of optimal scheduling of an electric bus (EB) fleet to cover a public transport timetable. …”

An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling by ALKETBI, SAIF

“…The uncertainty of time estimation is one of the most important problems which reduce any resource scheduler effectiveness. Genetic algorithm was chosen as the main methodology to build resource scheduler. …”
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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence by Al Rayhi, Nasser

“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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Allocation and re-allocation of data in a grid using an adaptive genetic algorithm by Mansour, N.

“…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
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A Tabu Search Algorithm For Maintenance Scheduling Of Generating Units by El-Amin, I.

“…A new heuristic algorithm based on the Tabu search has been proposed for the maintenance schedule (MS) of electric generation units. …”
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A Tabu Search Algorithm For Maintenance Scheduling Of Generating Units by Duffuaa, S. O.

“…A new heuristic algorithm based on the Tabu search has been proposed for the maintenance schedule (MS) of electric generation units. …”
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Efficient methods and techniques for the open-shop scheduling problem. (c2006) by Bou Ghosn, Steve

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An efficient and secure compression technique for data protection using burrows-wheeler transform algorithm by M Baritha Begum (17541483)

Efficient Approximate Conformance Checking Using Trie Data Structures by Awad, Ahmed

“…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …”
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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem by Haraty, Ramzi A.

“…It is a highly-constrained combinatorial problem that seeks to find a possible scheduling for the university course offerings. There are many algorithms and approaches adopted to solve this problem, but one of the effective approaches to solve it is the use of meta-heuristics. …”
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A method for test scheduling using an evolutionary approach. (c2000) by Noujaim, Jad

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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) by Moujabber, Bassam N.

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A distributed genetic algorithm for deterministic and stochastic labor scheduling problems by Mansour, Nashat

“…In this paper we present a unified formulation for these three labor scheduling problems and introduce a distributed genetic algorithm (DGA) that solves each of them. …”
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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

“…Moreover, the image pixels in different and more similar areas of the image are located next to one another in a group and classified using the specified thresholds. As a result, the embedding capacity in each class can increase by reducing the value of the difference between two consecutive pixels, and the distortion of the marked image can decrease after inserting the personal data using the DE method. …”
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Joint Inversion of Direct Current Resistivity and Seismic Refraction Data, using Local and Global Optimization Algorithms with Synthetic and Real Data Examples by unknown

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Using Machine Learning Algorithms to Forecast Solar Energy Power Output by Ali Jassim Lari (22597940)

“…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …”