Search Results - aco metaheuristic algorithm

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  1. 1
    Assessment of metaheuristic algorithms to optimize of mixed-model assembly line balancing problem with resource constraints

    Assessment of metaheuristic algorithms to optimize of mixed-model assembly line balancing problem with resource constraints by M.M., Razali, M. F. F., Ab Rashid, M. R. A., Make

    Published 2020
    “…Mixed-model assembly line balancing problem (MMALBP) is an NP-hard problem whichrequires an effective algorithm for solution. In this study, an assessment of metaheuristic algorithms to optimize MMALBP was conductedby using four popular metaheuristics , namely particle swarm optimization (PSO), simulated annealing (SA), ant colony optimization (ACO),and genetic algorithm (GA). …”
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  2. 2
    Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review

    Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review by See, Phen Chiak, Wong, Kuan Yew

    Published 2008
    “…In recent years, there is an increasing interest in solving QAPs using the general extension of heuristic methods called metaheuristics. Ant Colony Optimisation (ACO) has currently emerged as a new and promising metaheuristic. …”
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  3. 3
    Assessment of integrated assembly sequence planning and line balancing optimization using metaheuristic algorithms

    Assessment of integrated assembly sequence planning and line balancing optimization using metaheuristic algorithms by Mohd Fadzil Faisae, Ab Rashid, Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim

    Published 2024
    “…These algorithms include Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). …”
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  4. 4
    Ant colony optimization algorithm for rule based classification: Issues and potential

    Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…This paper presents a review of related work of ACO rule classification which emphasizes the types of ACO algorithms and issues. …”
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  5. 5
    Reactive approach for automating exploration and exploitation in ant colony optimization

    Reactive approach for automating exploration and exploitation in ant colony optimization by Allwawi, Rafid Sagban Abbood

    Published 2016
    “…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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  6. 6
    Unified strategy for intensification and diversification balance in ACO metaheuristic

    Unified strategy for intensification and diversification balance in ACO metaheuristic by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2017
    “…The performance of RACO is evaluated on the travelling salesman and quadratic assignment problems from TSPLIB and QAPLIB, respectively.Results based on a comparison of relative percentage deviation revealed the superiority of RACO over other well-known metaheuristics algorithms.The output of this study can improve the quality of solutions as exemplified by RACO.…”
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  7. 7
    A new strategy to improve the search performance of Max-Min Ant Aystem Algorithm when solving the Quadratic Assignment Problems

    A new strategy to improve the search performance of Max-Min Ant Aystem Algorithm when solving the Quadratic Assignment Problems by Phen, Chiak See

    Published 2010
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  8. 8
    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network

    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network by SALLIM, JAMALUDIN

    Published 2017
    “…Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. …”
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  9. 9
    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network

    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network by Sallim, Jamaludin

    Published 2017
    “…Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. …”
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  10. 10
    Hybrid ACO and SVM algorithm for pattern classification

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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  11. 11
    Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics

    Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

    Published 2023
    “…The popular optimization algorithms PSO, GA, and ACO were implemented on the CHFS model with ten optimization runs. …”
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  12. 12
    Power line faults classification by neural network train by Ant Colony Optimization

    Power line faults classification by neural network train by Ant Colony Optimization by Nasirudin, Mohd Syafiq

    Published 2017
    “…The characteristic of ACO algorithms is their explicit use of elements of previous solutions. …”
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  13. 13
    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…The successful work on hybridization of ACO and SA algorithms has led to the improved learning ability of ACO for classification. …”
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  14. 14
    Some Metaheuristics for Tourist Trip Design Problem

    Some Metaheuristics for Tourist Trip Design Problem by Son, N.T., Nguyet Ha, T.T., Jaafar, J.B., Anh, B.N., Giang, T.T.

    Published 2023
    “…We have built two metaheuristic algorithms based on the proposed approach, which are Genetic Algorithm (GA) and another is Ant Colony Optimization (ACO). …”
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  15. 15
    A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem

    A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem by M. F. F., Ab Rashid

    Published 2017
    “…The proposed Hybrid Ant-Wolf Algorithm (HAWA) is designed to overcome premature convergence in ACO. …”
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  16. 16
    Improvement DACS3 Searching Performance using Local Search

    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. …”
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  17. 17
    Ant system with heuristics for capacitated vehicle routing problem

    Ant system with heuristics for capacitated vehicle routing problem by Tan, Wen Fang

    Published 2013
    “…Specifically, the proposed methodology in this study is called Ant System with Heuristics (ASH) and it was developed based on the first ACO metaheuristic, known as Ant System (AS). The ASH algorithm is basically applied with its probabilistic decision rule and pheromone feedback to construct the sequences of customers to be visited in the CVRP solution. …”
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  18. 18
    Aco-based feature selection algorithm for classification

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The performance of the proposed algorithm was evaluated on 18 benchmark datasets from the University California Irvine (UCI) repository and nine (9) deoxyribonucleic acid (DNA) microarray datasets against 15 benchmark metaheuristic algorithms. …”
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  19. 19
    Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach

    Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…Drawing on a diverse dataset from a commercial building, encompassing vital input parameters such as Chilled Water Rate, Building Load, Cooling Water Temperature, Humidity, and Dew Point, the study conducts a comprehensive comparison of metaheuristic algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Barnacles Mating Optimizer (BMO), Harmony Search Algorithm (HSA), Differential Evolution (DE), Ant Colony Optimization (ACO), and the latest RIME algorithm). …”
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  20. 20
    A new minimum pheromone threshold strategy (MPTS) for max-min ant system

    A new minimum pheromone threshold strategy (MPTS) for max-min ant system by Wong, Kuan Yew, See, Phen Chiak

    Published 2009
    “…Among others is the ant colony optimization (ACO) algorithm, which was inspired by the foraging behavior of ants. …”
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