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  1. 1
    A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA)

    A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA) by Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

    Published 2024
    “…The optimization result was compared with well-established algorithms, the Pareto Envelope-based Selection Algorithm II (PESA2), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), and new algorithms, Multi-Objective Grasshopper Optimization Algorithm (MOGOA) and Multi-Objective Ant Lion Optimizer (MOALO). …”
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  2. 2
    Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization

    Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

    Published 2022
    “…Optimization using MFO has been conducted and the results was compared with well-established algorithm like Genetic Algorithm, Ant Colony Optimization and Particle Swarm Optimization. …”
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  3. 3
    Enhancement of Ant System Algorithm for Course Timetabling Problem

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…As the requirement of the Ant System Algorithm, the problem is modeled as a graph that can be used by the ant to deliver its pheromone. …”
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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
    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid

    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

    Published 2012
    “…In computational grid, job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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  6. 6
    Simulation of identifying shortest path walkway in library by using ant colony optimization

    Simulation of identifying shortest path walkway in library by using ant colony optimization by Chui Teng, Chan

    Published 2012
    “…A research is proposed based on Ant Colony Optimization for solving the shortest path problem in library.This is a research that the algorithm is aim to implement on a robot. …”
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  7. 7
    AntNet: a robust routing algorithm for data networks

    AntNet: a robust routing algorithm for data networks by Haseeb, Shariq, Sidek, Khairul Azami, Ismail, Ahmad Faris, Weng Kin, Lai, Yit Mei, Aw

    Published 2004
    “…AntNet is an innovative algorithm that may be used for data networks. …”
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  8. 8
    Ant colony optimization for solving solid waste collection scheduling problems

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

    Published 2009
    “…Approach: The implementation of Ant Colony Optimization (ACO) for solving solid waste collection problem as a VRPSD model was described. …”
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  9. 9
    An Efficient Improvement Of Ant Colony System Algorithm For Handling Capacity Vehicle Routing Problem

    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
    “…This paper presents an improvement of Ant Colony System (ACS) to solve this problem. In this study, the problem deals with a few vehicles which are used for transporting products to specific places. …”
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  10. 10
    Application of Moth-Flame Optimizer and Ant Lion Optimizer to Solve Optimal Reactive Power Dispatch Problems

    Application of Moth-Flame Optimizer and Ant Lion Optimizer to Solve Optimal Reactive Power Dispatch Problems by Rebecca Ng, Shin Mei, M. H., Sulaiman, Hamdan, Daniyal, Zuriani, Mustaffa

    Published 2018
    “…This paper presents the application of two nature-inspired meta-heuristic algorithms, namely moth-flame optimizer (MFO) and ant lion optimizer (ALO) in obtaining the optimal settings of control variables for solving optimal reactive power dispatch (ORPD) problems. …”
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  11. 11
    Chaotic ant swarm optimization for economic dispatch considering transmission losses / Amelia Abd Razak

    Chaotic ant swarm optimization for economic dispatch considering transmission losses / Amelia Abd Razak by Abd Razak, Amelia

    Published 2012
    “…The proposed method is tested on six generation unit systems and the results show that it is able to solve ED problem. CASO algorithm used in this study was implemented by using MATLAB 7.5.0 (R2007b). …”
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  12. 12
    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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  13. 13
    Ant Colony Optimization for Solving Solid Waste Collection Scheduling Problems

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

    Published 2009
    “…Approach: The implementation of Ant Colony Optimization (ACO) for solving solid waste collection problem as a VRPSD model was described. …”
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  14. 14
    An Ant Colony System for Solving DNA Sequence Design Problem in DNA Computing

    An Ant Colony System for Solving DNA Sequence Design Problem in DNA Computing by Farhaana, Yakop, Zuwairie, Ibrahim, Amar Faiz, Zainal Abidin, Zulkifli, Md. Yusof, Mohd Saberi, Mohamad, Khairunizam, Wan, Watada, Junzo

    Published 2013
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  15. 15
    A comparative study on ant-colony algorithm and genetic algorithm for mobile robot planning.

    A comparative study on ant-colony algorithm and genetic algorithm for mobile robot planning. by Rajendran, Piraviendran, Othman, Muhaini

    Published 2024
    “…Objectives include analyzing features of mobile robot planning and representing them in ACO and GA, implementation ACO and GA algorithms for solving routing problems using dataset, and evaluating their performance. …”
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  16. 16
    Strategic oscillation for exploitation and exploration of ACS algorithm for job scheduling in static grid computing

    Strategic oscillation for exploitation and exploration of ACS algorithm for job scheduling in static grid computing by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2015
    “…Exploitation and exploration mechanisms are the main components in metaheuristics algorithms. These mechanisms are implemented explicitly in ant colony system algorithm.The rate between the exploitation and exploration mechanisms is controlled using a parameter set by the users of the algorithm. …”
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  17. 17
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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  18. 18
    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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  19. 19
    Parallel distributed computational microcontroller system for adaptive antenna downlink transmitter power optimization

    Parallel distributed computational microcontroller system for adaptive antenna downlink transmitter power optimization by Sankar K.P., Tiong S.K., Koh S.P.J.

    Published 2023
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  20. 20
    Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi

    Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi by Jabbar Hayyawi, Mustafa

    Published 2016
    “…Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. …”
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