Search Results - (( development problem selection algorithm ) OR ( java simulation optimization algorithm ))

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  1. 1
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

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

    Published 2011
    “…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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  2. 2
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    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

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  3. 3
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  4. 4
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…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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  5. 5
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    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.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  6. 6
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…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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  7. 7
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…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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  8. 8
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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  9. 9
    Some metaheuristic algorithms for solving multiple cross-functional team selection problems

    Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

    Published 2022
    “…We can find solutions to the team selection problem in many different areas. The problem solver needs to scan across a large array of available solutions during their search. …”
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  10. 10
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…Further, the performances of the developed algorithms are assessed in solving selected practical problems in business, mechanical/manufacturing engineering and electrical engineering fields. …”
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  11. 11
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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  12. 12
    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…By taking the bus services in Universiti Teknologi MARA as sample, the research has used the genetic algorithm approach to solve the problem which is similar to the Travel Salesman Problem. …”
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  13. 13
    Improvement and performance analysis on statistical selection algorithms

    Improvement and performance analysis on statistical selection algorithms by Kweh, Yeah Lun, Othman, Mohamed

    Published 2006
    “…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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  14. 14
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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  15. 15
    An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective

    An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective by Mousavi, Seyed Mohsen, Sadeghi R., Kiarash, Lee, Lai Soon

    Published 2023
    “…The selected cases are the river pollution problem, the urban transit network design problem, and the resilience problem. …”
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  16. 16
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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  17. 17
    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…Hence, Robust Non- Grouped variable selection(RNGVS.RFCH) in the presence of high multicollinearity problem and outliers is developed. …”
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  18. 18
    Clonal selection algorithm for the cryptanalysis of a simple substitution cipher

    Clonal selection algorithm for the cryptanalysis of a simple substitution cipher by Ahmad, Badrisham, Maarof, Mohd. Aizaini, Ibrahim, Subariah, Kutty Mammi, Hazinah, Mohamed Amin, Muhalim, Z'aba, Muhammad Reza

    Published 2006
    “…The development of Clonal Selection Algorithm (CSA) is inspired by elements from clonal selection theories. …”
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  19. 19
    Development of a Tuneable Test Problem Generator for Assembly Sequence Planning and Assembly Line Balancing

    Development of a Tuneable Test Problem Generator for Assembly Sequence Planning and Assembly Line Balancing by M. F. F., Ab Rashid, Hutabarat, Windo, Tiwari, Ashutosh

    Published 2012
    “…However, there is a scarcity in works that focus on developing problems to test these algorithms. In optimisation algorithm development, testing algorithms by a broad range of test problems is crucial to identify their strengths and weaknesses. …”
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  20. 20
    Evolutionary algorithm with roulette-tournament selection for solving aquaculture diet formulation

    Evolutionary algorithm with roulette-tournament selection for solving aquaculture diet formulation by Abd Rahman, Rosshairy, Ramli, Razamin, Jamari, Zainoddin, Ku-Mahamud, Ku Ruhana

    Published 2016
    “…In this paper, a new selection operator is introduced for a real valued encoding problem, which specifically exists in a shrimp diet formulation problem.This newly developed selection operator is a hybrid between two well-known established selection operators: roulette wheel and binary tournament selection.A comparison of the performance of the proposed operator and the other existing operator was made for evaluation purposes.The result shows that the proposed roulette-tournament selection is better in terms of its ability to provide many good feasible solutions when a population size of 30 is used.Thus, the proposed roulette-tournament is suitable and comparable to established selection for solving a real valued shrimp diet formulation problem.The selection operator can also be generalized to any problems related to EA.…”
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