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  1. 321

    Parallel metaheuristic algorithm for exam timetabling by Mansour, Nashat

    Published 2010
    “…For large numbers of exams and students, sequential algorithms are likely to be time consuming. The purpose of this work is to present a parallel metaheuristic algorithm for producing good sub-optimal exam timetables in a reasonable time. …”
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  2. 322

    Application of Heuristic Algorithms for Multiuser Detection by Morra, H.

    Published 0000
    “…The new proposed structure brings several improvements when compared to both the conventional (matched filter) detector and the decorrelating detector. Additionally, the algorithm proposed here fairly approximates the performance of the optimal MUD detector with much reduced computational complexity.…”
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  3. 323

    Hybrid Interval Type-2 Fuzzy PID+I Controller for a Multi-DOF Oilwell Drill-String System by Abdelbaset Laib (16904688)

    Published 2022
    “…<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. …”
  4. 324

    Scalable Parallel Algorithms for FPT Problems by Abu-Khzam, Faisal N.

    Published 2006
    “…As a case study, optimal solutions to very large instances of the NP-hard vertex cover problem are computed. …”
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  5. 325

    Impact of Charging Electric Vehicles under Different State of Charge Levels and Extreme Conditions by Claude Ziad El-Bayeh (17542284)

    Published 2021
    “…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. …”
  6. 326

    Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach by Haitham Osman (11737057)

    Published 2025
    “…A comprehensive techno-economic analysis is conducted, supported by a machine learning-assisted optimization framework that combines artificial neural networks with genetic algorithms. …”
  7. 327

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

    Published 2016
    “…The results showed the proposed methodology outperformed existing algorithms in optimizing project durations and resources allocation. …”
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  8. 328
  9. 329

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

    Published 2004
    “…A novel combination of emergent algorithmic methods, powerful computational platforms and supporting infrastructure is described. …”
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  10. 330

    A new multimodulus blind equalization algorithm by Abrar, Shafayat

    Published 2004
    “…The phase-recovery and intersymbol interference optimization properties, exhibited by the proposed algorithm, are also discussed.…”
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  11. 331

    A simulated annealing algorithm for unit commitment by Mantawy, A.H.

    Published 1998
    “…This paper presents a simulated annealing algorithm (SAA) to solve the unit commitment problem (UCP). …”
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    article
  12. 332

    Genetic algorithms applications in load frequency control by Abdel-Magid, Y.L.

    Published 1995
    “…This paper deals with the application of genetic algorithms for optimizing the parameters of conventional automatic generation control (AGC) systems. …”
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  13. 333

    A SIMULATED ANNEALING ALGORITHM FOR THE CLUSTERING PROBLEM by Selim, S.Z.

    Published 2020
    “…In this paper we discuss the solution of the clustering problem usually solved by the K-means algorithm. The problem is known to have local minimum solutions which are usually what the K-means algorithm obtains. …”
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  14. 334

    Adaptive bias simulated evolution algorithm for placement by Youssef, H.

    Published 2001
    “…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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  15. 335

    A New Parallel Genetic Algorithm Model by Al-Somani, Turki F.

    Published 2020
    “…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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    article
  16. 336

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

    Published 2018
    “…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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  17. 337
  18. 338

    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

    Published 2022
    “…The slime mould algorithm (SMA) gives good results in finding the best solutions to optimization problems. …”
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  19. 339
  20. 340

    Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

    Published 2016
    “…The results show that our algorithm is able to produce 3D structures with good sub-optimal energy values. …”
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