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  1. 1
    Computational intelligence based power tracing for nondiscriminatory losses charge allocation and voltage stability improvement. / Zulkifli Abdul Hamid

    Computational intelligence based power tracing for nondiscriminatory losses charge allocation and voltage stability improvement. / Zulkifli Abdul Hamid by Abdul Hamid, Zulkifli

    Published 2013
    “…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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  2. 2
    Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing

    Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

    Published 2015
    “…One of the prominent intelligent algorithms is ant colony system (ACS) which is implemented widely to solve various types of scheduling problems. …”
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  3. 3
    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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  4. 4
    Heuristic factors in ant system algorithm for course timetabling problem

    Heuristic factors in ant system algorithm for course timetabling problem by Djamarus, Djasli, Ku-Mahamud, Ku Ruhana

    Published 2009
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  5. 5
    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
    “…Nevertheless, ACO also has several drawbacks that may reduce the classification accuracy and the computational time of the algorithm. 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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  6. 6
    QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs)

    QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs) by Moghanjoughi, Ayyoub Akbari, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir

    Published 2008
    “…In this paper, a new algorithm, Intelligent agent AntNet based Routing Algorithm (IANRA) is proposed to enhance load balancing strategy in Wireless Networks (WNs). …”
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  7. 7
    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim

    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

    Published 2008
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  8. 8
    Load balancing using enhanced ant algorithm in grid computing

    Load balancing using enhanced ant algorithm in grid computing by Abdul Nasir, Husna Jamal, Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2010
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  9. 9
    Nature-inspired parameter controllers for ACO-based reactive search

    Nature-inspired parameter controllers for ACO-based reactive search by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
    “…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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  10. 10
    Efficient and scalable ant colony optimization based WSN routing protocol for IoT

    Efficient and scalable ant colony optimization based WSN routing protocol for IoT by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2020
    “…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. …”
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  11. 11
    African Buffalo Optimization (ABO): A New Metaheuristic Algorithm

    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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  12. 12
    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management

    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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  13. 13
    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
    “…The performances of six (6) ant colony optimization variants were evaluated to select the base for the proposed model.Based on the results, Max-Min Ant System has been chosen as the base for the modification.The modified algorithm called RMMAS, was applied to TSPLIB95 data and results showed that RMMAS outperformed the standard MMAS.…”
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  14. 14
    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali

    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

    Published 2015
    “…In this thesis, we implement the modified ant colony programming (ACP) algorithm for solving the matrix Riccati differential equation (MRDE). …”
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  15. 15
    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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  16. 16
    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…The hybrid algorithm is termed as the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). …”
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  17. 17
    Scheduling Algorithm For Lot Movement in Semiconductor Wafer Fabrication

    Scheduling Algorithm For Lot Movement in Semiconductor Wafer Fabrication by Norzieyuswati, Md Zenal

    Published 2008
    “…Imitating the collective activities of ant colonies, an approach to constructing pheromone-based scheduling algorithm using Ant Colony Optimization for lot movement in semiconductor wafer fabrication process is propose to be implemented in SilTerra Malaysia.…”
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  18. 18
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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  19. 19
    Multi agent quality of service routing based on scheme ant colony optimization algorithm

    Multi agent quality of service routing based on scheme ant colony optimization algorithm by Baygi, Maassoumeh Javadi

    Published 2014
    “…The important new aspect of ACR-QoS is the combination of constraint-based routing and DiffServ architecture, in Swarm Intelligence (SI) structure where a set of artificial ants is used to determine the optimal path for each class to construct class-based routing tables. …”
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  20. 20
    A hybrid of ant colony optimization, genetic algorithm and flux balance analysis for optimization of succinic acid production in Escherichia coli

    A hybrid of ant colony optimization, genetic algorithm and flux balance analysis for optimization of succinic acid production in Escherichia coli by Tan, Jun Bin, Choon, Yee Wen, Moorthy, Kohbalan, Hasyiya Karimah, Adli, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Zuwairie, Ibrahim, Mohd Saberi, Mohamad

    Published 2023
    “…Ant colony optimization (ACO) is a swarm intelligent optimization that is inspired based on the natural foraging behavior of ant colony. …”
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