Search Results - (( solution construction based algorithm ) OR ( java simulation optimization algorithm ))*

Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. …”
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Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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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

“…The simulation is implemented with iFogSim and java programming language. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…This paper investigates the construction phase approach in which the sequential order of the courses/lectures applied several combination of graph heuristics to generate a population of initial solutions in curriculum-based course timetabling (CBCTT).The construction of population of initial solution is a prerequisite in a population-based metaheuristic implementation. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Utilizing the roulette wheel based social network search algorithm for substitution box construction and optimization by Kamal Z., Zamli, Alhadawi, Hussam S., Fakhrud Din, .

“…This paper introduces a new variant of a recent metaheuristic algorithm based on the Social Network Search algorithm (SNS), which is called the Roulette Wheel Social Network Search algorithm (SNS). …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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A hybrid adaptive harmony search with modified great deluge algorithm for school timetabling by Arbaoui, Billel

“…In Phase 1, heuristic rules refine the time assignment stage to improve an existing construction algorithm. Phase 2 adaptively tunes parameters based on iteration position, solution number, behavioral status, and parameter linkages. …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

“…(iii) It is a constructive-based meta-heuristic algorithm which means, the solution is incrementally constructed (step by step) until the complete solution is obtained (Noferesti and Shah-Hosseini, 2012). …”

Sequential constructive algorithm incorporate with fuzzy logic for solving real world course timetabling problem by Tan, Li June, Joe H. Obit, Leau, Yu Beng, Jetol Bolongkikit, Rayner Alfred

“…Sequential constructive algorithm is one of the popular methods for solving timetabling problems. …”
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Harmony annealing algorithm for curriculum-based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…An attempt to solve these problems was made via an approach broken down into two parts; first, constructive algorithm with saturation degree approach was used to ensure a feasible solution, where the hard constraints are satisfied.Secondly, Harmony annealing algorithm was used to further improve the results obtained.The algorithm produced results that were not comparatively better than those previously known as best solution.With 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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Construction of initial solution population for curriculum-based course timetabling using combination of graph heuristics by Wahid, Juliana, Mohd Hussin, Naimah

“…The construction of population of initial solution is a crucial task in population-based metaheuristic approach for solving curriculum-based university course timetabling problem because it can affect the convergence speed and also the quality of the final solution.This paper presents an exploration on combination of graph heuristics in construction approach in curriculum based course timetabling problem to produce a population of initial solutions.The graph heuristics were set as single and combination of two heuristics.In addition, several ways of assigning courses into room and timeslot are implemented.All settings of heuristics are then tested on the same curriculum based course timetabling problem instances and are compared with each other in terms of number of population produced.The result shows that combination of largest degree followed by saturation degree heuristic produce the highest number of population of initial solutions.The results from this study can be used in the improvement phase of algorithm that uses population of initial solutions…”
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Enhancing the Sorting Layers in the Initial Stage of High School Timetabling by Arbaoui, Billel, Wahid, Juliana, Abdul-Rahman, Syariza

“…KHE is an algorithm that generates initial solution of HSTP. …”
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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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Sequential Constructive Algorithm incorporate with Fuzzy Logic for Solving Real World Course Timetabling Problem by Tan, Li June, Joe Henry Obit, Leau, Yu Beng, Jetol Bolongkikit, Rayner Alfred

“…Sequential constructive algorithm is one of the popular methods for solving timetabling problems. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Constructing population of initial solutions for curriculum – based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…Future work will use the best settings of heuristics to the improvement phase in population-based improvement algorithm.…”
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