Search Results - optimal ((((((drop algorithm) OR (graph algorithm))) OR (colony algorithm))) OR (based algorithm))

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    Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Characteristics of jobs and resources to be used in evaluating the performance of the scheduling algorithm must reflect the dynamic nature of real grid environment.Static models of jobs and resources cannot be used to generate jobs and resources in simulating the grid environment because of the dynamic nature of the grid.This paper presents a new graph representation of jobs and resources which is practical for hybrid metaheuristic model implementation such as ant colony optimization and genetic algorithm.A dynamic model that can generate jobs and resources similar to the jobs and resources in the real grid environment is also proposed.Jobs and resources may join in or drop out from the grid.Stochastic analysis is performed on the characteristics of jobs and resources.A simulator based on the dynamic expected time to compute, has been developed and can be used as a benchmark.The simulator can generate jobs and resources with the characteristics of jobs and resources in the real grid environment.This will facilitates the evaluation of dynamic job scheduling algorithm.…”
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  3. 3

    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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    Monograph
  4. 4

    Congestion management based optimization technique using bee colony by Rahim M.A., Musirin I., Abidin I.Z., Othman M.M., Joshi D.

    Published 2023
    Subjects: “…Bee colony algorithm…”
    Conference Paper
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    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…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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    Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling by Shimailawi, Shatha Abdulhadi Muthana

    Published 2022
    “…Present graph models cannot generate schedule for the multi-objective GMS models while existing Pareto Ant Colony System (PACS) algorithms were not able to consider the two problems separately. …”
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    Thesis
  7. 7

    Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system by Mohammad Ata, Karimeh Ibrahim, Che Soh, Azura, Ishak, Asnor Juraiza, Jaafar, Haslina

    Published 2021
    “…This solution depending on applying the optimization on an optimal path while the traditional ACO is optimizing the random path based on the greedy algorithm hence we get the most optimal path. …”
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    Article
  8. 8

    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2015
    “…The African Buffalo Optimization (A.B.0) algorithm simulates the African buffalos' behaviour by encapsulation in a mathematical model; which solves a number of discrete optimization problems using graph-based route planning, job scheduling and it extends Swarm Intelligence paradigms. …”
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    Article
  9. 9

    A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network by Jamaludin, Sallim, Rozlina, Mohamed, Che, Yahaya, Roslina, Abdul Hamid

    Published 2018
    “…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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    Article
  10. 10

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

    Published 2011
    “…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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    Monograph
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    A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network by Jamaludin, Sallim, Rozlina, Mohamed, Roslina, Abd Hamid

    Published 2015
    “…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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    High Rise Building Evacuation Route Model Using DIJKSTRA'S Algorithm by Mohd Sabri, Nor Amalina

    Published 2015
    “…The main algorithms involve is Dijkstra’s algorithm and then an Ant Colony Optimization algorithm is used as hybrid versions of Dijkstra’s algorithm. …”
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    Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar by Vijyakumar, Kanendra Naidu

    Published 2015
    “…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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    Thesis
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    An efficient multi join query optimization for relational database management system using swarm intelligence approaches by Alsaedi, Ahmed Khalaf Zager

    Published 2016
    “…A directed acyclic graph, based on materialized query graph, aids in the optimization of algorithms and solving MJQO by removing non-promising QEP, which decreases the QEP combination space. …”
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    An efficient multi join query optimization for relational database management system using swarm intelligence approaches by Alsaedi, Ahmed Khalaf Zager

    Published 2016
    “…A directed acyclic graph, based on materialized query graph, aids in the optimization of algorithms and solving MJQO by removing non-promising QEP, which decreases the QEP combination space. …”
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    Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2017
    “…This process is a crucial task because it can affect the convergence speed and also the quality of the final solution (Rahnamayan, Tizhoosh, & Salama, 2007).This study able to produce a set of initial solution, therefore it is able to contribute to the improvement phase of approach that uses population of initial solutions such as ant colony optimization (ACO) (Socha, Joshua, & Michael, 2002), genetic algorithm (GA) (Lewis & Paechter, 2005), and harmony search algorithm (HSA) (Al-Betar & Khader, 2010).The approach in this study also shows that a feasible timetable can be found for numerous data set problems.…”
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    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
    “…Travelling salesman problem (TSP) is one the problems of NP-complete family, which means finding shortest complete close tour in the graph. This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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    Article
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    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

    Published 2023
    “…This algorithm synergizes the ABC algorithm and Artificial Rabbits Optimization (ARO) algorithm. …”
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    DNA sequence design for direct-proportional length-based DNA computing: Particle swarm optimization vs population based ant colony optimization by Zulkifli, Md. Yusof, Muhammad Arif, Abdul Rahim, Sophan Wahyudi, Nawawi, Kamal, Khalil, Zuwairie, Ibrahim

    Published 2012
    “…In this study, particle swarm optimization (PSO) and population-based ant colony optimization (P-ACO) are employed to design DNA sequences with different lengths and the results obtained are compared. …”
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