Search Results - (( colony optimisation method algorithm ) OR ( simulation optimization method algorithm ))

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  1. 1

    Tool path generation of contour parallel based on ant colony optimisation by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

    Published 2016
    “…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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  2. 2

    Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review by See, Phen Chiak, Wong, Kuan Yew

    Published 2008
    “…In recent years, there is an increasing interest in solving QAPs using the general extension of heuristic methods called metaheuristics. Ant Colony Optimisation (ACO) has currently emerged as a new and promising metaheuristic. …”
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  3. 3

    Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment by Tang, Phooi Wah, Choon, Yee Wen, Mohamad, Mohd Saberi, Deris, Safaai, Napis, Suhaimi

    Published 2015
    “…This paper proposes a hybrid of the artificial bee colony (ABC) algorithm and the minimisation of metabolic adjustment (MOMA) to predict an optimal set of solutions in order to optimise the production rate of succinate and lactate. …”
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  4. 4

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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  5. 5

    Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus by Abu Bakar, Nordin, Abdul Kudus, Rosnawati

    Published 2009
    “…The complexity is due to the fact that little is known about the learning process that can be simulated in a machine. In this study two methods have been chosen to navigate a simulated robot to a target point; namely, Ants Colony Optimisation (ACO) and the Fuzzy Approach. …”
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  6. 6

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…This thesis presents works on swarm intelligence algorithms that are inspired by real echolocation of a colony of bats and its performance evaluation to solve optimisation problems. …”
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  7. 7

    Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

    Published 2013
    “…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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  8. 8

    A Modified Bats Echolocation-Based Algorithm for Solving Constrained Optimisation Problems by N. M., Yahya, Tokhi, M. O.

    Published 2017
    “…The proposed algorithm is applied to solve the constrained optimisation problems coupled with penalty function method as constraint handling technique. …”
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    Application of adaptive bats sonar algorithm for solving a single objective of practical business optimisation problem PROBLEM by Nafrizuan, Mat Yahya, M. Nafis, O. Z.

    Published 2016
    “…The proposed algorithm can thus be an effective method for solving of single objective optimisation problems.…”
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  11. 11

    Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

    Published 2023
    “…This algorithm named JAABC5ROC is the enhancement of Artificial Bee Colony (ABC) variant, JA-ABC5 by combining with Rate of Change (ROC)\. …”
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  12. 12

    Optimisation of vehicle routing problem with time windows using Harris Hawks optimiser by Chai, S. W., Kamaluddin, M. R., Ab Rashid, M. F. F.

    Published 2022
    “…This problem has been widely studied and optimised using different methods. Since the performance of algorithms in different problems is dissimilar, the study to optimise the VRPTW is ongoing. …”
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    Evaluating JA-ABC5 hyperparameter optimisation with classifiers by Ravindran, Nadarajan, Noorazliza, Sulaiman, Junita, Mohamad-Saleh

    Published 2024
    “…Because of its simplicity, flexibility, and robustness, the Artificial Bee Colony (ABC) algorithm, a swarm intelligence-based optimisation method, has been widely applied in a variety of fields. …”
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  16. 16

    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm by Muhammad Arif, Abdullah

    Published 2019
    “…Furthermore, a case study was conducted to validate the proposed EE-ASP model and the performance of the optimisation algorithms. The MFO performance was compared with three frequently used meta-heuristics algorithms in ASP, namely Ant Colony Optimisation (ACO), Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO). …”
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  17. 17

    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

    Published 2023
    “…However, the FGCDR produced a substantial amount of redundant and insignificant features. The ant colony optimisation (ACO) algorithm have been used to select feature subset. …”
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  18. 18

    Seamless vertical handover technique for vehicular ad-hoc networks using artificial bee colony-particle swarm optimisation by Abdulwahhab, Mohanad Mazin

    Published 2019
    “…Firstly, we proposed a multi-criteria artificial bee colony hybrid with particle swarm optimisation algorithm (MC ABC-PSO) for evaluating the information gathered from the mobile nodes in the handover. …”
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    Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique by Lai V., Huang Y.F., Koo C.H., Ahmed A.N., Sherif M., El-Shafie A.

    Published 2024
    “…The Artificial Bee Colony (ABC) outcomes satisfied demand at 61.36%, 59.47% with the Particle Swarm Optimisation (PSO), 55.68% with the real-coded Genetic Algorithm (GA), and 23.5 percent with the binary GA. …”
    Article