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  1. 1

    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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    Article
  2. 2

    Comfort and energy consumption optimization in smart homes using bat algorithm with inertia weight by Mohamad Razwan, Abdul Malek, Nor Azlina, Ab. Aziz, Alelyani, Salem, Mohana, Mohamed, Farah Nur Arina, Baharudin, Zuwairie, Ibrahim

    Published 2022
    “…Moreover, the comfort level achieved by BA with exponential inertia weight is found to be better than previously reported works using firefly algorithm, genetic algorithm, ant colony optimization, and artificial bee colony algorithm. …”
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    Article
  3. 3

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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    Thesis
  4. 4

    Multi-Robot Learning with Bat Algorithm With Mutation (Bam) by Chandrathevan, Sathiamurthy

    Published 2022
    “…BAT algorithm uses echolocation technique like bats to generate bat population and random data is generated, the robot then traverses and the distance is calculated which is compared to the distance from the obstacle. …”
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    Undergraduates Project Papers
  5. 5

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…Secondly, two meta-heuristics, namely, Bi-Objective Gravitational Search Algorithm (BOGSA) and Bi-Objective Bat Algorithm (BOBAT), were combined to form a (BOGS-BAT) algorithm. …”
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    Thesis
  6. 6

    Application of adaptive bats sonar algorithm to minimise car side impact design by Tan, Hon Seong

    Published 2017
    “…This project was focusing on the modification of bats sonar algorithm (BSA) and renamed to adaptive bats sonar algorithm (ABSA) due to some limitations of previous algorithm. …”
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    Undergraduates Project Papers
  7. 7

    Extended Bat Algorithm (EBA) as an improved searching optimization algorithm by Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Luhur, Bayuaji, Nor Rul Hasma, Abdullah, Zainah, Md. Zain, Indra, Riyanto

    Published 2018
    “…This paper presents a new searching technique by using a new variant of Bat Algorithm (BA) known as Extended Bat Algorithm (EBA). …”
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    Book Chapter
  8. 8

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

    Published 2016
    “…Recently, a new metaheuristic search Bat algorithm has become quite popular due its tendency towards convergence to optimal points in the search trajectory by using echo-location behavior of bats as its random walk. …”
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    Thesis
  9. 9
  10. 10

    Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

    Published 2017
    “…The other recommendation are to increase the number of random pixels for initial population step of Bat algorithm. …”
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    Thesis
  11. 11

    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
    “…This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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    Article
  12. 12

    Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

    Published 2023
    “…Hence, this thesis will utilize Non-Systematic Weighted Random 2 Satisfiability incorporating with Binary Artificial Bee Colony algorithm in Discrete Hopfield Neural Network. …”
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    Thesis
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  14. 14

    An improved bees algorithm local search mechanism for numerical dataset by Al-Dawoodi, Aras Ghazi Mohammed

    Published 2015
    “…Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. …”
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    Thesis
  15. 15

    Bat Algorithm Based Hybrid Filter-Wrapper Approach by Taha A.M., Chen S.-D., Mustapha A.

    Published 2023
    “…This paper presents a new hybrid of Bat Algorithm (BA) based on Mutual Information (MI) and Naive Bayes called BAMI. …”
    Article
  16. 16

    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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    Thesis
  17. 17

    A true annealing approach to the marriage in honey-bees optimization algorithm by Teo, Jason Tze Wi, Hussein A. Abbass

    Published 2003
    “…Marriage in Honey-Bees Optimization is a new swarm intelligence technique inspired by the marriage process of honey-bees. …”
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    Article
  18. 18

    An empirical study of double-bridge search move on subset feature selection search of bees algorithm by Al-dawoodi, Aras Ghazi Mohammed, Mahmuddin, Massudi

    Published 2017
    “…The algorithm performs combination of exploitative neighbourhoods and random explorative search. …”
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    Article
  19. 19

    Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm by Mohamad Fadzil, Nur Hamisha Helanie

    Published 2025
    “…Random insertion applied as a neighbourhood operator to enhance the local search capabilities within the algorithm. …”
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    Student Project
  20. 20

    Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

    Published 2014
    “…The bees are classified into three agents: the employed bee which carries the information about the food source, the onlooker bee watching the dance of the employed bees within the hive and making the decision to choose a food source based on the dances, and the scout bee, performing random search for the food sources. …”
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    Conference or Workshop Item