Search Results - (( web simulation optimization algorithm ) OR ( java application scheduling algorithm ))
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…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
Published 2014“…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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Final Year Project -
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…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
Published 2006“…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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Intelligent Web caching using neurocomputing and particle swarm optimization algorithm
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Conference or Workshop Item -
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques
Published 2014“…Second, both the constructive procedure (CP) and the complementary procedure (CCP) heuristic algorithms computed the optimization considering only the execution path that has been predicted by the runtime path prediction method for criteria selection, eight QoS characteristics are suggested after investigating related works on the area of web service and web service composition. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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9
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…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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Search engine optimization algorithms for page ranking: comparative study
Published 2018“…:No doubt that every second in our daily routine, the number of visitors that connect to the internet increase day by day due to the fast growing of World Wide Web. Until this day there are more than 11.3 billion web pages in the World Wide Web. …”
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Article -
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Batch mode heuristic approaches for efficient task scheduling in grid computing system
Published 2016“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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Thesis -
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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Academic Exercise -
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A new ant based rule extraction algorithm for web classification
Published 2011“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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Monograph -
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Classroom finder system with student availability, space and time constraint
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Final Year Project / Dissertation / Thesis -
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Smart student timetable planner
Published 2025“…Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. 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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Final Year Project / Dissertation / Thesis -
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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Smart Routing For Solid Waste Collection
Published 2023“…Finally, the conclusion highlights the accomplishments of the project, including the successful development of the route optimization algorithm and the web-based application. …”
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Final Year Project Report / IMRAD -
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…Experimental evaluation confirmed that the proposed grid scheduling algorithms possess a high degree of optimality in performance, efficiency and scalability.…”
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