Search Results - (( using optimization based algorithm ) OR ( software solution using algorithm ))

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  1. 1
    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
    “…This paper proposes Opposition-based Whale Optimization Algorithm (OWOA) to optimize solution problem in 0/1 Knapsack. …”
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  2. 2
    Opposition-based Whale Optimization Algorithm

    Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

    Published 2018
    “…The OWOA use the Opposition-based method to enhance Whale Optimization Algorithm (WOA) performance. …”
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  3. 3
    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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  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
    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
    “…ACO algorithm is the best solution because it included the optimization technique to optimized the result based on the data criteria needs. …”
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  6. 6
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…By using the MOGA optimization approach in mode Frontier, multi-objective optimization could be done by coupling with several software environment; this does not require any modification of the original model. …”
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  7. 7
    Maintain optimal configurations for large configurable systems using multi-objective optimization

    Maintain optimal configurations for large configurable systems using multi-objective optimization by Jamil, Muhammad Abid, Alsadie, Deafallah, Nour, Mohamed K., Awang Abu Bakar, Normi Sham

    Published 2022
    “…The different approaches have been presented by Search-based software engineering (SBSE) to resolve the software engineering issues into computational solutions using some metaheuristic approach. …”
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  8. 8
    Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy

    Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy by Ehteram, Mohammad, Banadkooki, Fatemeh Barzegari, Fai, Chow Ming, Moslemzadeh, Mohsen, Sapitang, Michelle, Ahmed, Ali Najah, Irwan, Dani, El-Shafie, Ahmed

    Published 2021
    “…The Seagull Optimization Algorithm was then used to find two heading parameters of the TPHRs. …”
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  9. 9
    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference

    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

    Published 2018
    “…Specifically, the modified model-based optimal control problem is resulted. Here, the conjugate gradient approach is used to solve the modified model-based optimal control problem, where the optimal solution of the model used is calculated repeatedly, in turn, to update the adjusted parameters on each iteration step. …”
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  10. 10
    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
    “…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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  11. 11
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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  12. 12
    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment

    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment by M. F., Masrom, N. M. A., Ghani, M. O., Tokhi

    Published 2021
    “…This paper presents investigations into the development of an interval type-2 fuzzy logic control (IT2FLC) mechanism integrated with particle swarm optimization and spiral dynamic algorithm. The particle swarm optimization and spiral dynamic algorithm are used for enhanced performance of the IT2FLC by finding optimised values for input and output controller gains and parameter values of IT2FLC membership function as comparison purpose in order to identify better solution for the system. …”
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  13. 13
    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion

    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

    Published 2018
    “…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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  14. 14
    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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  15. 15
    Product assembly sequence optimization based on genetic algorithm

    Product assembly sequence optimization based on genetic algorithm by Yasin, Azman, Puteh, Nurnasran, Daud, Ruslizam, Omar, Mazni, Syed-Abdullah, Sharifah Lailee

    Published 2010
    “…Genetic algorithm (GA) is a search technique used in computing to find approximate solution to optimization and search problem based on the theory of natural selection. …”
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  16. 16
    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim

    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

    Published 2021
    “…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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  17. 17
    Optimal power flow using hybrid firefly and particle swarm optimization algorithm

    Optimal power flow using hybrid firefly and particle swarm optimization algorithm by Khan, Abdullah, Hizam, Hashim, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi

    Published 2020
    “…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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  18. 18
    A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm

    A population division based multi-task optimization algorithm for solving multiple-team formation problem based on Tiki-Taka optimization algorithm by Ahmmed, Mohammad Badal, Kamal Z., Zamli

    Published 2022
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  19. 19
    Development of improved metaheuristic algorithms for modelling and control of a flexible manipulator system

    Development of improved metaheuristic algorithms for modelling and control of a flexible manipulator system by Nasir, Ahmad Nor Kasruddin, Ahmad, Mohd Ashraf, Raja Ismail, R. M.T., Muhammad Hamka, Embong

    Published 2019
    “…The aim of the single type algorithms is to improve the algorithms capability to find an optimal solution. …”
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  20. 20
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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