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  1. 1
    A comparative performance analysis of computational intelligence techniques to solve the asymmetric travelling salesman problem

    A comparative performance analysis of computational intelligence techniques to solve the asymmetric travelling salesman problem by Odili, Julius Beneoluchi, Noraziah, Ahmad, Zarina, M.

    Published 2021
    “…The comparative algorithms in this study employ different techniques in their search for solutions to ATSP: the African Buffalo Optimization employs the modified Karp–Steele mechanism, Model-Induced Max-Min Ant Colony Optimization (MIMM-ACO) employs the path construction with patching technique, Cooperative Genetic Ant System uses natural selection and ordering; Randomized Insertion Algorithm uses the random insertion approach, and the Improved Extremal Optimization uses the grid search strategy. …”
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  2. 2
    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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  3. 3
    Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches

    Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
    “…The exploration versus exploitation dilemma rises in ACO search.Reactive max-min ant system algorithm is a recent proposition to automate the exploration and exploitation.It memorizes the search regions in terms of reactive heuristics to be harnessed after restart, which is to avoid the arbitrary exploration later.This paper examined the assumption that local heuristics are useless when combined with local search especially when it applied for combinatorial optimization problems with rugged fitness landscape.Results showed that coupling reactive heuristics with k-Opt local search algorithms produces higher quality solutions and more robust search than max-min ant system algorithm.Well-known combinatorial optimization problems are used in experiments, i.e. traveling salesman and quadratic assignment problems. …”
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  4. 4
    Ant colony optimization in dynamic environments

    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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  5. 5
    An exploration technique for the interacted multiple ant colonies optimization framework

    An exploration technique for the interacted multiple ant colonies optimization framework by Aljanaby A., Ku-Mahamud K.R., Norwawi N.Md.

    Published 2024
    Conference Paper
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  6. 6
    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
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  7. 7
    Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms

    Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

    Published 2025
    “…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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  8. 8
    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
    “…Thereafter, various suggestions have been made to improve the performance of the ACO algorithm. One of them is through the development of the max–min ant system (MMAS) algorithm. …”
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  9. 9
    Cross-layer design using multi-channel system in WiMAX mesh networks

    Cross-layer design using multi-channel system in WiMAX mesh networks by Al-Hemyari, Ali, Ng, Chee Kyun, Noordin, Nor Kamariah, Ismail, Alyani, Khatun, Sabira, Jamuar, Sudhanshu Shekhar

    Published 2008
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  10. 10
    Interacted Multiple Ant Colonies for Search Stagnation Problem

    Interacted Multiple Ant Colonies for Search Stagnation Problem by Aljanabi, Alaa Ismael

    Published 2010
    “…The experimental results show the superiority of the proposed approach than existing one colony ant algorithms like the ant colony system and max-min ant system. …”
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  11. 11
    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin

    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin by Alsahag, Ali Mohammed, Mohd Ali, Borhanuddin, Noordin, Nor Kamariah, Mohamad, Hafizal

    Published 2014
    “…Simulation results show that the proposed algorithm manages to optimize the overall system utilization while at the same time guarantee the maximum latency requirements for real-time traffic.…”
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  12. 12
    Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks

    Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks by Al-Humairi, Ali Zuhair Abdulameer

    Published 2009
    “…This thesis proposes an optimized strategy namely cross-layer design in routing algorithms used find the best route for all SSs and scheduling algorithms, used to assign a time slot for each possible node transmission. …”
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  13. 13
    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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  14. 14
    Training size optimization with reduced complexity in cell-free massive MIMO system

    Training size optimization with reduced complexity in cell-free massive MIMO system by Ullah, Sayeid M. Sahid, Mahyiddin, Wan Amirul Wan Mohd, Zakaria, Nur Azira, Latef, Tarik Abdul, Noordin, Kamarul Ariffin, Dimyati, Kaharudin

    Published 2019
    “…In this paper, we proposed to use training size optimization in cell-free massive MIMO system. …”
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  15. 15
    Reactive memory model for ant colony optimization and its application to TSP

    Reactive memory model for ant colony optimization and its application to TSP by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2014
    “…Ant colony optimization is one of the most successful examples of swarm intelligent systems. …”
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  16. 16
    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks

    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

    Published 2013
    “…Finally, the FuzSAHO decision algorithim is optimized for real-time application, by using a new handover criteria, namely queue length besides RSSI and MS velocity. …”
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  17. 17
    Ant colony algorithm for job scheduling in grid computing

    Ant colony algorithm for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Abdul Nasir, Husna Jamal

    Published 2010
    “…Scheduling jobs to resources in grid computing 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.This will lead to resourccs having high workload and stagnation may occur if computational times of the processed jobs are high.This paper proposed an enhanced ant colony optimization algorithm for jobs and resources scheduling in grid computing.The proposed ant colony algorithm for job scheduling in the grid environment combines the techniques from Ant Colony System and Max - Min Ant System.The algorithm focuses on local pheromone trail update and the trail limit values. …”
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  18. 18
    An Exploration Technique for the Interacted Multiple Ant Colonies Optimization Framework

    An Exploration Technique for the Interacted Multiple Ant Colonies Optimization Framework by Aljanaby, A, Ku-Mahamud, KR, Norwawi, NM

    Published 2024
    “…These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system.…”
    Proceedings Paper
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  19. 19
    Design Optimization of a Gas Turbine Engine for Marine Applications: Off-Design Performance and Control System Considerations

    Design Optimization of a Gas Turbine Engine for Marine Applications: Off-Design Performance and Control System Considerations by Machmudah, A., Lemma, T.A., Solihin, M.I., Feriadi, Y., Rajabi, A., Afandi, M.I., Abbasi, A.

    Published 2022
    “…The modeling of gains as a function of plant variables is presented. Meta-heuristic optimizations, namely a genetic algorithm (GA) and a whale optimization algorithm (WOA), are applied to optimize the designed control system. …”
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  20. 20
    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network

    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

    Published 2010
    “…In addition, the proposed algorithm improved the system throughput up to 68% in the multi-transceiver system and 28% in the single-transceiver system.…”
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