Search Results - (( problem based evaluation algorithm ) OR ( java simulation optimization algorithm ))

Search alternatives:

Refine Results
  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
    “…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. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  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
    “…The simulation is implemented with iFogSim and java programming language. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  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). …”
    Get full text
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  4. 4
    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. …”
    Review
    Save to List
    Saved in:
  5. 5
    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. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    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. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  7. 7
    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.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  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. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems

    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems by Yusof, Zulkifli Md., Ibrahim, Zuwairie, Adam, Asrul, Azmi, Kamil Zakwan Mohd, Ab. Rahman, Tasiransurini, Muhammad, Badaruddin, Ab. Aziz, Nor Azlina, Abd Aziz, Nor Hidayati, Mokhtar, Norrima, Shapiai, Mohd Ibrahim, Muhammad, Mohd Saberi

    Published 2018
    “…To control and exploration and exploitation of the SEDESKF algorithm, the distance is normalized. The performance of the SEDESKF algorithm is compared against the existing combinatorial SKF algorithm based on a set of Traveling Salesman Problem (TSP).…”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems

    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems by Zuwairie, Ibrahim, Zulkifli, Md. Yusof, Asrul, Adam, Kamil Zakwan, Mohd Azmi, Tasiransurini, Ab Rahman, Badaruddin, Muhammad, Nor Azlina, Ab. Aziz, Norrima, Mokhtar, Mohd Ibrahim, Shapiai, Mohd Saberi, Mohamad

    Published 2018
    “…To control and exploration and exploitation of the SEDESKF algorithm, the distance is normalized. The performance of the SEDESKF algorithm is compared against the existing combi-natorial SKF algorithm based on a set of Traveling Salesman Problem (TSP).…”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique

    Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

    Published 2008
    “…The new algorithm is based on the ant colony system and utilizes average and maximum pheromone evaluation mechanisms. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions

    Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions by Badaruddin, Muhammad, Zuwairie, Ibrahim, Kamarul Hawari, Ghazali, Mohd Riduwan, Ghazali, Kian, Sheng Lim, Sophan Wahyudi, Nawawi, Nor Azlina, Ab. Aziz, Marizan, Mubin, Norrima, Mokhtar

    Published 2014
    “…This paper presents a performance evaluation of Vector Evaluated Gravitational Search Algorithm (VEGSA), namely VEGSA-I and VEGSA-II algorithms, for multi-objective optimization problems. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  15. 15
    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems

    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems by Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof

    Published 2012
    “…This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  16. 16
    Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods

    Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods by Salih, Rawia Tahrir

    Published 2021
    “…The evaluation criteria of Many Objective Optimization algorithm (MaOO) play a critical role in evaluating the competition MaOO algorithms. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems

    Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems by Zulkifli, Md. Yusof, Zuwairie, Ibrahim, Ismail, Ibrahim, Kamil Zakwan, Mohd Azmi, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd. Aziz, Mohd Saberi, Mohamad

    Published 2015
    “…The performance of the proposed distance evaluated SKF (DESKF) is compared against two other discrete population-based optimization algorithms, namely, binary particle swarm optimization (BPSO) and binary gravitational search algorithm (BGSA). …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  18. 18
    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance

    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    Hybrid performance measures and mixed evaluation method for data classification problems

    Hybrid performance measures and mixed evaluation method for data classification problems by Hossin, Mohammad

    Published 2012
    “…For a systematic analysis, the mixed evaluation method is implemented into two stages. First, the hybrid measures are compared and analyzed against the accuracy measure based on their produced-values through different classification problems with different class distribution problems. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints

    A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints by Jia, Hui Ong, Teo, Jason Tze Wi

    Published 2016
    “…The second experiment allows these algorithms to run up to the full 10000N evaluations. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: