Search Results - (( course optimization method algorithm ) OR ( java application scheduling algorithm ))

Smart student timetable planner by Wong, Xin Tong

“…A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. …”
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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

“…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

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A harmony search algorithm for university course timetabli by Al-Betar, Mohammed Azmi, Khader, Ahamad Tajudin

“…The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. …”
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Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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Meta-Heuristic Algorithms for Learning Path Recommender at MOOC by Son, N.T., Jaafar, J., Aziz, I.A., Anh, B.N.

“…We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. …”
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Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling by Al-Betar, Mohammed Azmi

“…Harmony Search Algorithm (HSA) is a recent metaheuristic population-based method. …”
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Harmony great deluge for solving curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…University course timetabling which has been determined as non deterministic polynomial problem that accept widely as problem that are intractable.An efficient algorithm does not exist that is guaranteed to find an optimal solution for such problems.The design of good algorithm to find new methods and techniques to solve such problem is a very active area of research.This paper presents the adaption of the hybridizing between harmony search with great deluge algorithm for solving curriculum-based course timetabling problems.The algorithm can be adapted to the problem.Results were not comparatively better than those previously known as best solution.Proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.…”
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Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid by Wahid, Juliana

“…The real data of UUM CAS timetable was analyzed and processed using the proposed algorithms. The result shows that the quality cost of UUM CAS course timetabling produced by the proposed algorithms is better compared to the course timetable produced by the ready-made software package. …”
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Evaluate the performance of university timetabling problem with various artificial intelligence techniques by Hooi, Charmaine Wai Yee

“…Over time, numerous algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and other approaches have been introduced to address the challenges of optimizing class schedules. …”
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Classroom finder system with student availability, space and time constraint by Loh, Yong Bin

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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

“…The proposed approach utilizes genetic algorithms to dynamically produce optimized timetables based on individual student needs, with real-time data scraping from 'iCRESS' ensuring the system stays up to date with the latest course information for accurate timetable generation. …”
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Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables by Abdullah S., Shaker K., Shaker H.

“…The performance of the approach is tested with over two sets of benchmark datasets, that is, enrolment-based course timetabling and curriculum-based course timetabling (UD1) in comparison with a set of state-of-the-art methods from the literature. …”

Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction by Ismanto, Edi, Ab Ghani, Hadhrami, Md Saleh, Nurul Izrin

“…Genetic algorithms for hyperparameter optimization significantly contributed, with the GA + LSTM + ADAGRAD model achieving 88% and 87% accuracy in the 7th and 9th models for BBB course data. …”
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