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  1. 1

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

    Published 2008
    “…Problem statement: Ant Colony System (ACS) is the most popular algorithm used to find a shortest path solution in Traveling Salesman Problem (TSP). …”
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  2. 2

    DACS3:Embedding Individual Ant Behavior in Ant Colony System by Ali Othman, Zulaiha, Md Rais, Helmi, Hamdan, Abdul Razak

    Published 2008
    “…Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). …”
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  3. 3

    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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  4. 4

    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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  5. 5

    DACS3: Embedding Malaysian Individual Ant Behavior in Ant Colony System by Ali Othman, Zulaiha, Md Rais, Helmi, Hamdan, Abdul Razak

    Published 2009
    “…Their ability as a colony, to find paths to food sources has inspired the development of algorithms known as Ant Colony Systems (ACS). The principle of cooperation forms the backbone of such algorithms, commonly used to find solutions to problems such as the Traveling Salesman Problem (TSP). …”
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    Citation Index Journal
  6. 6

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

    Published 2019
    “…ACO for clustering (ACOC) is an ant colony system (ACS) algorithm inspired by the foraging behavior of ants for clustering tasks. …”
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  7. 7
  8. 8

    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
  9. 9
  10. 10

    Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP). by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2007
    “…Thus, this new level of pheromone updates which manipulating and empowering the searching experiences of individual ants can improve the current ACS algorithm. Traveling Salesman Problem (TSP) was used as a case study to show the capability of the algorithm in order to find the best solution in terms of the shortest distance. …”
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  11. 11

    Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2015
    “…Hybrid metaheuristic algorithms have the ability to produce better solution than stand-alone approach and no algorithm could be concluded as the best algorithm for scheduling algorithm or in general, for combinatorial problems.This study presents the low and high level hybridization of ant colony system and genetic algorithm in solving the job scheduling in grid computing.Two hybrid algorithms namely ACS(GA) as a low level and ACS+GA as a high level are proposed.The proposed algorithms were evaluated using static benchmarks problems known as expected time to compute model. …”
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  12. 12

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
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    Thesis
  13. 13

    Strategies DACS3 Increasing its Performances by Ali Othman, Zulaiha, Md Rais, Helmi, Hamdan, Abdul Razak

    Published 2009
    “…Ant Colony System (ACS) is the most popular algorithm used to find a shortest path solution in Traveling Salesman problem (TSP). …”
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  14. 14

    FINDING SHORTEST PATH FOR DYNAMIC PUTTING PROBLEM USING ANT COLONY OPTIMISATION by Nor Akmal, Abdul Aziz

    Published 2005
    “…Specifically. this thesis is intended to develop a system that can display the shortest path by the used of two algorithm in ACO which were Ant System (AS) and Ant Colony System (ACS). …”
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    Final Year Project Report / IMRAD
  15. 15

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

    Published 2019
    “…Ant Colony Optimization (ACO) is a generic algorithm, which has been widely used in different application domains due to its simplicity and adaptiveness to different optimization problems. …”
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  16. 16

    Ant colony optimization for solving solid waste collection scheduling problems by Ismail, Zuhaimy, Loh, S. L.

    Published 2009
    “…But the percentage deviations of averages from the associated best cost are 0.1322 and 0.7064 for ACS and SA. The results indicated that for all demand ranges, proposed ACO algorithm showed better performance than SA algorithm. …”
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  17. 17

    Ant Colony Optimization for Solving Solid Waste Collection Scheduling Problems by Ismail, Zuhaimy, Loh, Ser Lee

    Published 2009
    “…But the percentage deviations of averages from the associated best cost are 0.1322 and 0.7064 for ACS and SA. The results indicated that for all demand ranges, proposed ACO algorithm showed better performance than SA algorithm. …”
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  18. 18

    An Efficient Improvement Of Ant Colony System Algorithm For Handling Capacity Vehicle Routing Problem by Modhi Lafta Mutar, Mohd Aboobaider, Burhanuddin, Asaad Shakir Hameed, Yusof, Norzihani, Hussein Jameel Mutashar

    Published 2020
    “…The proposed study seeks to find the best solution of CVRP by using improvement ACS with the accompanying targets: (1) To decrease the distance as long distances negatively affect the course of the process since it consumes a great time to visit all customers. (2) To implement the improvement of ACS algorithm on new data from the database of CVRP. …”
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  19. 19

    An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…However, ACOC suffers from high diversification in which the algorithm cannot search for best solutions in the local neighbourhood. …”
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  20. 20

    Suitability Factor on the Capacitated Vehicle Routing Problem by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2010
    “…One of the most popular solutions is using Ant Colony System (ACS) algorithm. …”
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