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  1. 1
    Hybrid harmony search algorithm for continuous optimization problems

    Hybrid harmony search algorithm for continuous optimization problems by Ala’a Atallah, Hamad Alomoush

    Published 2020
    “…Harmony Search (HS) algorithm has been extensively adopted in the literature to address optimization problems in many different fields, such as industrial design, civil engineering, electrical and mechanical engineering problems. …”
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  2. 2
    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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  3. 3
    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning

    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

    Published 2019
    “…GWO-HS was evaluated using 24 classical benchmark functions with 30 state-of-the-art benchmark functions from CEC2014. …”
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  4. 4
    Enhancing three variants of harmony search algorithm for continuous optimization problems

    Enhancing three variants of harmony search algorithm for continuous optimization problems by Alomoush, Alaa A., Alsewari, Abdulrahman A., Kamal Z., Zamli, Alrosan, Ayat, Alomoush, Waleed, Alissa, Khalid

    Published 2021
    “…Harmony search (HS) is a recognized meta-heuristic algorithm with an efficient exploration process. …”
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  5. 5
    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions

    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

    Published 2022
    “…This paper aims to compare the performance of two metaheuristic algorithms which are Jaya Algorithm (JA) and Cuckoo Search (CS) using some common benchmark functions. …”
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  6. 6
    Solving 0/1 Knapsack Problem Using Hybrid HS and Jaya Algorithms

    Solving 0/1 Knapsack Problem Using Hybrid HS and Jaya Algorithms by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2018
    “…In this research, a new hybrid algorithm of Harmony search and Jaya search algorithms applied on 0/1 Knapsack problem to find a near optimal results. …”
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  7. 7
    A new HMCR parameter of harmony search for better exploration

    A new HMCR parameter of harmony search for better exploration by Nur Farraliza, Mansor, Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S

    Published 2015
    “…However, when performing a local search, the harmony search algorithm can be easily trapped in the local optima. …”
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  8. 8
    An improved bat algorithm with artificial neural networks for classification problems

    An improved bat algorithm with artificial neural networks for classification problems by Rehman Gillani, Syed Muhammad Zubair

    Published 2016
    “…Metaheuristic search algorithms have been used for quite a while to optimally solve complex searching problems with ease. …”
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  9. 9
    Performance evaluation of vector evaluated gravitational search algorithm II

    Performance evaluation of vector evaluated gravitational search algorithm II by Muhammad, B., Ibrahim, Z., Ghazali, K.H., Ghazali, M.R., Mubin, M., Mokhtar, M.

    Published 2014
    “…The VEGSAII algorithm uses a number of populations of particles. …”
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  10. 10
    Fuzzy adaptive emperor penguin optimizer for global optimization problems

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…A test suite of twelve benchmark test functions and three global optimization problems: Team Formation Optimization (TFO), Low Autocorrelation Binary Sequence (LABS), and Modified Condition/ Decision coverage (MC/DC) test case generation problem were solved using the proposed algorithm. …”
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  11. 11
    Assessing the symbiotic organism search variants using standard benchmark functions

    Assessing the symbiotic organism search variants using standard benchmark functions by Nurul Asyikin, Zainal, Fakhrud, Din, Kamal Z., Zamli

    Published 2019
    “…Symbiotic Organism Search (SOS) is one of the latest meta-heuristic algorithms created to solve optimization problems. …”
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  12. 12
    Comparative implementation of the benchmark Dejong 5 function using flower pollination algorithm and the African buffalo optimization

    Comparative implementation of the benchmark Dejong 5 function using flower pollination algorithm and the African buffalo optimization by Odili, Julius Beneoluchi, Noraziah, Ahmad

    Published 2019
    “…In addition, it explores the Dejong 5 function with the hope of attracting the attention of the research community to evaluate the capacity of the two comparative algorithms as well as the Dejong 5 function. …”
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  13. 13
    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions

    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

    Published 2014
    “…Owing to the fact that they are new and much of their relative performance are still unknown (as compared to other established meta-heuristic algorithms), Bacterial Foraging Optimization Algorithm (BFO) and Bat Algorithm (BA) have been adopted for comparison using the 12 selected benchmark functions. …”
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  14. 14
    A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS)

    A comparative study of heuristic methods to solve Traveling Salesman Problem (TPS) by Lim, Yai Fung, Hong, Pei Yee, Ramli, Razamin, Khalid, Ruzelan

    Published 2011
    “…The objective of the TSP is to find the shortest path that reaches all the cities which are interconnected with each other by straight lines.The symmetric TSP is used and the distance between two cities is calculated by using Euclidean equation.In this study, three heuristic methods, namely simulated annealing (SA), tabu search (TS) and reactive tabu search (RTS) are used to solve TSP.SA is a generic probabilistic meta-algorithm for the global optimization problem and TS is a meta-heuristic search technique that guides a local search procedure to explore the solution space beyond local optimality. …”
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  15. 15
    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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  16. 16
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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  17. 17
    An Application of Cuckoo Search Algorithm for Solving Combined Economic and Emission Dispatch Problem

    An Application of Cuckoo Search Algorithm for Solving Combined Economic and Emission Dispatch Problem by M. H., Sulaiman, Zuriani, Mustaffa, Nor Rul Hasma, Abdullah

    Published 2015
    “…This paper presents the application of Cuckoo Search Algorithm (CSA) in solving the combined economic and emission (CEED) dispatch problem. …”
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  18. 18
    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem

    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

    Published 2022
    “…A test suite of twelve optimization benchmark test functions and three global optimization problems (Team Formation Optimization - TFO, Low Autocorrelation Binary Sequence - LABS, and Modified Condition/Decision Coverage - MC/DC test case generation) were solved using the proposed algorithm. …”
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  19. 19
    Global gbest guided-artificial bee colony algorithm for numerical function optimization

    Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. …”
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  20. 20
    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin

    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin by Jinudin, Muhammad Imza Fakhri

    Published 2018
    “…All algorithms are written and executed using Maple 16 software. …”
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