Search Results - (( based interactive bee algorithm ) OR ( based optimization based algorithm ))

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  1. 1

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
    “…However, very few strategies have been proposed for sequence-based t-way. This paper presents statistical analysis on the performance of Bees Algorithm against the other sequence t-way strategies, in order to generate test cases.…”
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    Article
  2. 2

    Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2019
    “…This is called hybrid artificial bee colony (HABC) strategy, which is based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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    Article
  3. 3

    HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A., Capretz, L.F., Imam, A.A., Balogun, A.O.

    Published 2021
    “…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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    Article
  4. 4

    HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A., Capretz, L.F., Imam, A.A., Balogun, A.O.

    Published 2021
    “…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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    Article
  5. 5

    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

    Published 2018
    “…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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    Thesis
  6. 6

    Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2020
    “…Complementing to the earlier researches, this paper proposes a new pairwise test suite generation called Pairwise Hybrid Artificial Bee Colony (PhABC) strategy based on hybridize of an Artificial Bee Colony (ABC) algorithm with a Particle Swarm Optimization (PSO) algorithm. …”
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    Article
  7. 7

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

    Published 2019
    “…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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    Thesis
  8. 8
  9. 9

    HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2020
    “…The input variables for a realworld software may diverge in how they strongly influence variable strength (VS) interaction can achieve that effectively. This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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    Article
  10. 10

    HABC: Hybrid artificial bee colony for generating variable T-way test sets by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2020
    “…The input variables for a realworld software may diverge in how they strongly influence variable strength (VS) interaction can achieve that effectively. This paper proposed a hybrid artificial bee colony (HABC) strategy based on the hybrid artificial bee colony algorithm and practical swarm optimization to generate optimal test suite of variable strength interaction. …”
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    Article
  11. 11

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…Therefore this research proposed a novel model for artificial neuro-glial networks and swarm-inspired algorithm for autonomous robots’ communication. Artificial neuro-glial networks is proposed to be combined in the swarm-based communication algorithm to provide a human-like model for the robot's communication and optimization.…”
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    Monograph
  12. 12

    Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

    Published 2018
    “…The results showed that the proposed PSO algorithm outperformed the other algorithms in terms of the optimal solutions and the convergence.…”
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    Article
  13. 13

    Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization by Salih, Sinan Q., Alsewari, Abdulrahman A., Al-Khateeb, Bellal, Mohamad Fadli, Zolkipli

    Published 2019
    “…Most of these algorithms were inspired either by nature or the behavior of certain swarms, such as birds, ants, bees, or even bats. …”
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    Book Chapter
  14. 14

    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- stead of a sophisticated controller that governs the global behavior of the system, the swarm intelligence principle is based on many unsophisticated entities (for example such as ants, termites, bees etc.) that cooperate and interact in order to exhibit a desired behav- ior. …”
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    Thesis
  15. 15

    Sequence-based interaction testing implementation using Bees Algorithm by Mohd Hazli M.Z., Kamal Z. Z., Rozmie R. O.

    Published 2023
    Subjects: “…Bees Algorithm…”
    Conference paper
  16. 16

    Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation by Kamal Z., Zamli, Mohd Hazli, Mohammed Zabil

    Published 2013
    “…Using combinatorial method, our strategy adopted Bees Algorithm (BA) to generate the test data for sequence t-way. …”
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    Article
  17. 17

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

    Published 2018
    “…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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    Article
  18. 18

    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
    “…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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    Article
  19. 19

    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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    Conference or Workshop Item
  20. 20

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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    Thesis