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  1. 1
    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib

    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

    Published 2019
    “…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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  2. 2
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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  3. 3
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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  4. 4
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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  5. 5
    Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system

    Opposition-based spiral dynamic algorithm with an application to optimize type-2 fuzzy control for an inverted pendulum system by Nasir, Ahmad Nor Kasruddin, Abdul Razak, Ahmad Azwan

    Published 2022
    “…Spiral Dynamic Algorithm (SDA) is a group-based optimization algorithm formulated based on the concept of a natural spiral phenomenon on earth. …”
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  6. 6
    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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  7. 7
    Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing

    Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

    Published 2017
    “…In this paper, we combined MBO and elitism to solve the Combinatorial Interaction Testing (CIT) problem i.e. to find a set of minimum test case which is an NP-Complete problem. This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. …”
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  8. 8
    An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz

    An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz by Nor Azlina, Ab. Aziz

    Published 2017
    “…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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  9. 9
    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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  10. 10
    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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  11. 11
    An Orchestrated Survey on T-Way Test Case Generation Strategies Based on Optimization Algorithms

    An Orchestrated Survey on T-Way Test Case Generation Strategies Based on Optimization Algorithms by Alsewari, Abdulrahman A., Kamal Z., Zamli

    Published 2014
    “…This paper presents an orchestrated survey of the existing OpA t-way strategies as Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Algorithm (ACA), Particle Swarm Optimization based strategy (PSTG), and Harmony Search Strategy (HSS). …”
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  12. 12
    A swarm intelligent approach for multi-objective optimization of compact heat exchangers

    A swarm intelligent approach for multi-objective optimization of compact heat exchangers by Yousefi M., Yousefi M., Martins Ferreira R.P., Darus A.N.

    Published 2023
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  13. 13
    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem

    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

    Published 2023
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  14. 14
    Harmony search-based robust optimal controller with prior defined structure

    Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

    Published 2013
    “…For further assessment, the proposed design strategy is then employed to design a control law for an electrical DC drive velocity controller used as a benchmark problem for the recent PSO-based and genetic algorithm optimization (GAO)-based robust controllers. …”
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  15. 15
    Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim

    Deterministic and stochastic inventory routing problems with backorders using artificial bee colony / Huda Zuhrah Ab Halim by Huda Zuhrah , Ab Halim

    Published 2019
    “…A new MILP for DSIRPB is formulated and used within the algorithm. The DSIRPB is modeled as stochastic dynamic programming and solved using hybrid rollout algorithm. …”
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  16. 16
    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
    “…Two main aspects are used to classify the evolutionary algorithm variants: population-based and evolutionary strategies (variation and replacement). …”
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  17. 17
    Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing

    Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing by Din, Fakhrud, Kamal Z., Zamli

    Published 2017
    “…Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. …”
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  18. 18
    Iteration strategy and ts effect towards the performance of population based metaheuristics

    Iteration strategy and ts effect towards the performance of population based metaheuristics by Nor Azlina, Ab. Aziz, Nor Hidayati, Abdul Aziz, Azlan, Abd Aziz, Tasiransurini, Abdul Rahman, Wan Zakiah, Wan Ismail, Zuwairie, Ibrahim

    Published 2020
    “…Three parent algorithms, namely, particle swarm optimization (PSO), gravitational search algorithm (GSA), and simulated Kalman filter (SKF) are used in this work to find a general pattern of the effect of iteration strategy towards the performance of population-based algorithms. …”
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  19. 19
    Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control

    Opposition-based manta ray foraging algorithm for global optimization and its application to optimize nonlinear type-2 fuzzy logic control by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abdul Ghani, Mohammad Osman, Tokhi

    Published 2024
    “…The proposed opposition-based MRFO (OMRFO) algorithms are applied to optimize the IT2FLC control design for a laboratory-scaled inverted pendulum system. …”
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  20. 20
    Hybrid Migrating Birds Optimization Strategy for t-way Test Suite Generation

    Hybrid Migrating Birds Optimization Strategy for t-way Test Suite Generation by Hasneeza, L. Zakaria, Kamal Z., Zamli, Fakhrud, Din

    Published 2019
    “…This paper presents the implementation of meta-heuristic search algorithms that are Migrating Birds Optimization (MBO) algorithm and Genetic Algorithm (GA) hybrid to a t-way test data generation strategy. …”
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