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  1. 1
    Particle swarm optimization (PSO) for CNC route problem

    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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  2. 2
    Optimization of mycelium growth using genetic algorithm for multi-objective functions

    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…Trade-off between the objectives, exist for the optimization process. To solve this issues, multi-objective genetic algorithm was chosen as the methodology for this project, specifically using NSGA-ii algorithm. …”
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  3. 3
    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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  4. 4
    Solving multi-task optimization problems using the sine cosine algorithm

    Solving multi-task optimization problems using the sine cosine algorithm by Kamal Z., Zamli, Kader, Md. Abdul

    Published 2022
    “…Often, optimization problems are solved using metaheuristic algorithms which provide good enough solution within reasonable execution time and limited resources. …”
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  5. 5
    Solving 0/1 Knapsack Problem using Opposition-based Whale Optimization Algorithm (OWOA)

    Solving 0/1 Knapsack Problem using Opposition-based Whale Optimization Algorithm (OWOA) by Alamri, Hammoudeh S., Zamli, Kamal Z., Ahmad Firdaus, Zainal Abidin, Mohd Faizal, Ab Razak

    Published 2019
    “…Practically, as many metaheuristic algorithms, Whale Optimization Algorithm (WOA) may fail in local optimum solution. …”
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  6. 6
    Towards Software Product Lines Optimization Using Evolutionary Algorithms

    Towards Software Product Lines Optimization Using Evolutionary Algorithms by Jamil, Muhammad Abid, K Nour, Mohamed, Alhindi, Ahmed Hasan, Awang Abu Bakar, Normi Sham, Arif, Muhammad, Muhammad Aljabri, Tareq

    Published 2019
    “…Testing in SPL is regarded as a combinatorial optimization problem. Evolutionary algorithms were reported to provide good results in such class of problems. …”
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  7. 7
    An improved genetic bat algorithm for unconstrained global optimization problems

    An improved genetic bat algorithm for unconstrained global optimization problems by Muhammad Zubair, Rehman, Kamal Z., Zamli, Abdullah, Nasser

    Published 2020
    “…Metaheuristic search algorithms have been in use for quite a while to optimally solve complex searching problems with ease. …”
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  8. 8
    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. …”
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  9. 9
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…The proposed fuzzy adaptive teaching learning-based optimization algorithm uses three measures from the search space, namely, quality measure, diversification measure, and intensification measure. …”
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  10. 10
    An adaptive flower pollination algorithm for minimizing software testing redundancy

    An adaptive flower pollination algorithm for minimizing software testing redundancy by M. N., Kabir, Ali, Jahan, Alsewari, Abdulrahman A., Kamal Z., Zamli

    Published 2017
    “…In this paper, we present an adaptive flower pollination algorithm for solving an optimization problem, i.e., minimization of software testing redundancy. …”
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  11. 11
    African Buffalo Optimization

    African Buffalo Optimization by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2016
    “…This is an introductory paper to the newly-designed African Buffalo Optimization (ABO) algorithm for solving combinatorial and other optimization problems. …”
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  12. 12
    A Comparative Study of African Buffalo Optimization and Randomized Insertion Algorithm for Asymmetric Travelling Salesman's Problem

    A Comparative Study of African Buffalo Optimization and Randomized Insertion Algorithm for Asymmetric Travelling Salesman's Problem by Odili, Julius Beneoluchi, M. N. M., Kahar, Shahid, Anwar, Azrag, M. A. K.

    Published 2015
    “…The Randomized Insertion and African Buffalo Optimization algorithms employ two different methods in attempting solutions to ATSP: the African Buffalo Optimization employs the modified Karp-Steele approach while the Randomized Insertion uses random insertion approach. …”
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  13. 13
    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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  14. 14
    Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman

    Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman by Isman, Muhammad Iskandar

    Published 2017
    “…Therefore, in this research, will be use Ant Colony Optimization (ACO) algorithm as an optimize technique that provide a shortest path of defining a successor that is their highest value of criteria. …”
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  15. 15
    Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization

    Modeling and optimization of multi-holes drilling path using Particle Swarm Optimization by Ab Rashid, Mohd Fadzil Faisae, Nik Mohamed, Nik Mohd Zuki, Romlay, Fadhlur Rahman Mohd, Razali, Akhtar Razul, Asmizam, Mokhtar

    Published 2018
    “…Later the problem is optimized using Particle Swarm Optimization (PSO) and compared with other algorithms including the new metaheuristics algorithms. …”
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  16. 16
    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers

    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2022
    “…Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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  17. 17
    A Comparison of Particle Swarm optimization and Global African Buffalo Optimization

    A Comparison of Particle Swarm optimization and Global African Buffalo Optimization by Adam Kunna Azrag, Mohammed, Tuty Asmawaty, Abdul Kadir, Noorlin, Mohd Ali

    Published 2020
    “…The performance of Particle Swarm Optimization (PSO) brings attention to the field of algorithms when deals with different optimization problems. …”
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  18. 18
    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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  19. 19
    African Buffalo Optimization and the Randomized Insertion Algorithm for the Asymmetric Travelling Salesman’s Problems

    African Buffalo Optimization and the Randomized Insertion Algorithm for the Asymmetric Travelling Salesman’s Problems by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad, Odili, Esther Abiodun

    Published 2016
    “…This paper presents a comparative study of the African Buffalo Optimization algorithm and the Randomized Insertion Algorithm to solving the asymmetric Travelling Salesman’s Problem with the overall objective of determining a better method to solving the asymmetric Travelling Salesman’s Problem instances. …”
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  20. 20
    Comparative analysis of sine cosine and social network search-based algorithm for software test redundancy reduction optimization

    Comparative analysis of sine cosine and social network search-based algorithm for software test redundancy reduction optimization by Mekeng, Ambros Magnus Rudolf, Kamal Z., Zamli, Muhammad Zarlis, .

    Published 2024
    “…Addressing this issue as an optimization problem, many existing works adopts metaheuristic algorithms to eliminate redundancy. …”
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