Search Results - (( developing set bees algorithm ) OR ( java implication based algorithm ))

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  1. 1

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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  2. 2

    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2019
    “…Supplementing to earlier research work, this paper proposed 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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  3. 3

    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2019
    “…Supplementing to earlier research work, this paper proposed 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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  4. 4

    Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

    Published 2017
    “…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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  5. 5
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    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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  8. 8

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

    Published 2019
    “…The inventory holding cost is assumed to be product specific and only incurred at the assembly plant. An Artificial Bee Colony (ABC) algorithm is proposed for the problem. …”
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  9. 9

    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

    Published 2020
    “…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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  10. 10
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    Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

    Published 2023
    “…In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
    Review
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  13. 13

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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  14. 14

    Model and metaheuristics for robotic two-sided assembly line balancing problems with setup times by Li, Zixiang, Janardhanan, Mukund Nilakantan, Tang, Qiuhua, Ponnambalam, S. G.

    Published 2019
    “…A comprehensive study with 13 algorithms demonstrates that the two variants of artificial bee colony algorithm and migrating bird optimization algorithm are capable to achieve the optimality for small-size instances and to obtain promising results for large-size instances.…”
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    A krill herd behaviour inspired load balancing of tasks in cloud computing by Hasan, Raed Abdulkareem, Mohammed, Muamer N.

    Published 2017
    “…The performance of the suggested Krill-LB was benchmarked against that of Honey Bee Behavior Load Balancing (HBB-LB), Kill Herd, and Round Robin algorithms.…”
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  17. 17

    Optimization of supply chain management by simulation based RFID with XBEE Network by Soomro, Aftab Ahmed

    Published 2015
    “…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. This algorithm computes the optimal results of objective functions in a scientific manner. …”
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  18. 18

    Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach by Quadros, Jaimon Dennis, Khan, Sher Afghan, T., Prashanth

    Published 2021
    “…The data comprising of massive input output was achieved using the response surface methodology (RSM) based central composite design (CCD). Backpropagation algorithm (BP), artificial bee colony (ABC), and genetic algorithm (GA) models were used to train the neural network (NN) parameters using the data collected from the CCD-based response equation. …”
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