Search Results - (( problem based scheduling algorithm ) OR ( java application optimization algorithm ))

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

“…Offloading heavy data size to a remote node introduces the problem of additional delay due to transmission. 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

“…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which lead to the resources having high workload or the time taken to process a job is high.This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system.The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism.The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element.The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job.EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form.The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. …”
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Development of Simulated Annealing Based Scheduling Algorithm for Two Machines Flow Shop Problem by M., Muziana, Kamal Z., Zamli

“…Viewing as optimization problem and focusing on two machines, this research aims to develop a new Simulated Annealing based scheduling algorithm, called SA2M, for flow shop problem. …”
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A Modified Giffler and Thompson Genetic Algorithm on the Job Shop Scheduling Problem by Lee, Hui Peng, Salim, Sutinah

“…The goal of this research is to study an efficient scheduling method based on Genetic Algorithm (GA) to address JSSP. …”
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A sports tournament scheduling problem: Exploiting constraint-based algorithm and neighborhood search for the solution by Razamin, Ramli, Soong, Cai Juan, Haslinda, Ibrahim

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Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm by Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

“…Existing multi-objective Generator Maintenance Scheduling (GMS) models have considered unit commitment problem together with unit maintenance problem based on a periodic maintenance strategy. …”
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Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

“…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

“…As a member of the NP Problem, an exact algorithm to solve the course scheduling problem is not available to date. …”
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Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems by Umar, Umar Ali

“…Genetic algorithm has recorded of huge success in solving NP-Complete optimization problems with similar nature to this problem. …”
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A survey : particle swarm optimization-based algorithms for grid computing scheduling systems. by Ambursa, Faruku Umar, Latip, Rohaya

“…Each scheduling algorithm is described and discussed under the suitable category.…”
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Enhancing Market-Based Scheduling Algorithm on Globally Distributed Web Servers Using Least Suitable Sealed Bid Technique by Al-Ewiwi, Mahmoud

“…Scheduling of a multiple distributed servers is considered as a complex problem.considered as NP-complete problem,where no single efficient algorithm guaranteed to produce optimal results.This thesis investigates on how to find optimal solution for distribute system,by implementing market based scheduling Algorithm(MBSA).On implementing the MBSA, a new auction technique which is the least suitable sealed bid auction will be introduced.it is found that least suitable sealed bid technique will give the close-to-optimum solution.In the implementation, cooperative agents were used as a middleware between web servers and stand-alone schedulers. …”
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Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

“…The complexity of scheduling problem is considered as a nondeterministic polynomial complete (NP-complete) problem and therefore, an intelligent algorithm is required to achieve better scheduling solution. …”
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Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

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Innovative crossover and mutation in a genetic algorithm based approach to a campus bus driver scheduling problem with break consideration and embedded overtime by Ramli, Razamin, Ibrahim, Haslinda, Lim, Tze Shung

“…The unfairness of job distribution and the ineffectiveness of break-time assignment among bus drivers are factors identified as problem issues in the bus driver management in a university campus environment.The issues affect the quality of the bus service which then pointed to the efficiency or inefficiency of the bus driver scheduling system.Thus, this study investigates the problem and constraints connected to bus driver scheduling activities as a case in a campus environment.Therefore, we developed an efficient bus driver scheduling model based on the Genetic Algorithm (GA) approach. …”
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A hybrid constraint-based programming approach to design a sports tournament scheduling by Soong, Chai Juan, Ramli, Razamin, Ibrahim, Haslinda

“…Subsequently,previous work related to the problem is discussed. Thus, we present an innovative hybrid of a constraint-based algorithm and a neighbourhood search, which is an exploration into alternative and improved methodology in the problem of sports tournament scheduling with special multiple constraints. …”
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Enhanced utility accrual scheduling algorithms for adaptive real time system. by Othman, Muhammad Fauzan, Ahmad, Idawaty

“…Problem statement: This study proposed two utility accrual real time scheduling algorithms named as Preemptive Utility Accrual Scheduling (PUAS) and Non-preemptive Utility Accrual Scheduling (NUAS) algorithms. …”
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A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA) by Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…The (EE-HFS) optimization has been carried out using the Multi-Objective Dragonfly Algorithm (MODA). The optimization result was compared with well-established algorithms, the Pareto Envelope-based Selection Algorithm II (PESA2), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), and new algorithms, Multi-Objective Grasshopper Optimization Algorithm (MOGOA) and Multi-Objective Ant Lion Optimizer (MOALO). …”
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