Search Results - optimal ((acs algorithm) OR (_ algorithm))*

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  1. 1

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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    Thesis
  2. 2

    Path Optimization For Cooperative Multi-Head 3d Printing by Cheong, Kah Jun

    Published 2020
    “…Therefore, to solve the LPOP, two algorithms are proposed, the modified AS algorithm and the modified ACS algorithm. …”
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    Final Year Project / Dissertation / Thesis
  3. 3

    Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…Ant colony optimization (ACO) is a swarm algorithm inspired by different behaviors of ants. …”
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    Article
  4. 4
  5. 5

    An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town by Nor Rafidah, Mohamad

    Published 2005
    “…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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    Thesis
  6. 6

    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

    Published 2020
    “…Swarm intelligence algorithms have been applied in solving these problems including the Ant Colony System (ACS) which is one of the ant colony optimization variants. …”
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    Thesis
  7. 7

    Modified ACS centroid memory for data clustering by Jabbar, Ayad Mohammed, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2019
    “…Ant Colony Optimization for Clustering (ACOC) is a swarm algorithm inspired from nature to solve clustering issues as optimization problems. …”
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    Article
  8. 8

    Embedding Malaysian House Red Ant Behavior into an Ant Colony System by Ali Othman, Zulaiha, Md Rais, Helmi, Hamdan, Abdul Razak

    Published 2008
    “…This research aims to improve the algorithm by embedding individual Malaysian House Red Ant behavior into ACS. …”
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    Citation Index Journal
  9. 9

    New heuristic function in ant colony system for the travelling salesman problem by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
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    Conference or Workshop Item
  10. 10

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Recently, in line with the upcoming field called Search based Software Engineering (SBSE), many newly strategies have been developed adopting specific optimization algorithm (e.g. Genetic Algorithm (GA), Ant Colony (AC), Simulated Annealling (SA), Particle Swarm Optimization, and Harmony Search Algorithm (HS) as their basis in an effort to generate the most optimal solution. …”
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    Article
  11. 11

    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2022
    “…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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    Article
  12. 12

    Scheduling jobs in computational grid using hybrid ACS and GA approach by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Metaheuristics algorithms show very good performance in solving various job scheduling problems in computational grid systems.However, due to the complexity and heterogeneous nature of resources in grid computing, stand-alone algorithm is not capable to find a good quality solution in reasonable time.This study proposes a hybrid algorithm, specifically ant colony system and genetic algorithm to solve the job scheduling problem.The high level hybridization algorithm will keep the identity of each algorithm in performing the scheduling task.The study focuses on static grid computing environment and the metrics for optimization are the makespan and flowtime.Experiment results show that the proposed algorithm outperforms other stand-alone algorithms such as ant system, genetic algorithms, and ant colony system for makespan.However, for flowtime, ant system and genetic algorithm perform better.…”
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    Conference or Workshop Item
  13. 13

    Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin by Mohd Zainol Abidin, Nor Syakila

    Published 2014
    “…In the proposed MLFNN, Firefly Algorithm (FA) was employed as the optimizer and search tools of the MLFNN training parameters. …”
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    Article
  14. 14

    Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy by Ehteram M., Banadkooki F.B., Fai C.M., Moslemzadeh M., Sapitang M., Ahmed A.N., Irwan D., El-Shafie A.

    Published 2023
    “…Decision making; Natural language processing systems; Bat algorithms; Heading policy; Multi-reservoir operation; Multi-reservoir systems; Optimization algorithms; Power- generations; Salp swarms; Seagull optimization algorithm; Swarm algorithms; Two-point; Optimization…”
    Article
  15. 15

    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement by Karami, Mahdi

    Published 2011
    “…The genetic algorithm technique is explained and the real number representation of genetic algorithm is modeled. …”
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    Thesis
  16. 16

    Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2020
    “…This paper presents a new hybrid Ant-Miner classification algorithm and ant colony system (ACS), called ACS-Ant Miner. …”
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    Article
  17. 17

    New heuristic function in ant colony system algorithm by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza, Yusof, Yuhanif, Mahmuddin, Massudi, Alobaedy, Mustafa Muwafak

    Published 2012
    “…NP-hard problem can be solved by Ant Colony System (ACS) algorithm.However, ACS suffers from pheromone stagnation problem, a situation when all ants converge quickly to one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic value to calculate the probability of choosing the next node.However, the heuristic value is not updated throughout the process to reflect new information discovered by the ants.This paper proposes a new heuristic function for the Ant Colony System algorithm that can reflect new information discovered by ants.The credibility of the new function was tested on travelling salesman and grid computing problems.Promising results were obtained when compared to classical ACS algorithm in terms of best tour length for the travelling sales-man problem. …”
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    Conference or Workshop Item
  18. 18

    An enhanced ant colony system algorithm for dynamic fault tolerance in grid computing by Saufi, Bukhari

    Published 2020
    “…Ant colony system (ACS), a variant of ant colony optimization (ACO), is one of the promising algorithms for fault tolerance due to its ability to adapt to both static and dynamic combinatorial optimization problems. …”
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    Thesis
  19. 19

    Applying DACS3 in the Capacitated Vehicle Routing Problem by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2010
    “…Ant Colony System (ACS) is a well known optimization algorithm to find a good route solution for logistics and transportation industries such as Traveling Salesman Problem (TSP) or Vehicle Routing Problem (VRP), for the company maximize the efficiency and resource. …”
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    Conference or Workshop Item
  20. 20

    Improvement DACS3 Searching Performance using Local Search by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2009
    “…Several versions of metaheuristic ACOs’ have been developed through several improvement processes to produce better algorithm. Past research has proposed a Dynamic Ant Colony System with Three Level Updates (DACS3) algorithm that embedding a Malaysian House Red Ant behavior into current ACS. …”
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