Search Results - (( using functional testing algorithm ) OR ( using optimisation based algorithm ))
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1
A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem
Published 2021“…Their convergence characteristic and computational efficiency were analysed and compared with eight widely used metaheuristic algorithms, with the superiority validated using the Wilcoxon signed-rank test. …”
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Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions
Published 2014“…The improved VEPSO algorithms have been subjected to a series of numerical experiments based on ZDT benchmark datasets. …”
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3
Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The superior performances of the developed bats echolocation-inspired algorithms are verified through rigorous tests with optimisation benchmark test functions and problems. …”
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4
Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation
Published 2019“…The Bees Algorithm is a population-based optimisation algorithm inspired by the food foraging behaviour of honey bees. …”
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5
Optimization of multi-holes drilling path using particle swarm optimization
Published 2022“…One way to improve the multi-hole drilling is by optimising the tool path in the process. This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. …”
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6
Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…As for multi-objective functions associated with the optimisation problem, a weight-sum method is typically used to determine each objective function's coefficient factors (CF). …”
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7
Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems
Published 2016“…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm, and Genetic Algorithm (GA). …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems
Published 2018“…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems
Published 2018“…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). …”
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10
Tiki-taka algorithm: a novel metaheuristic inspired by football playing style
Published 2021“…The algorithm was tested using 19 benchmark functions and five engineering design problems. …”
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Adaptive Spiral Dynamics Metaheuristic Algorithm for Global Optimisation with Application to Modelling of a Flexible System
Published 2016“…The proposed algorithm is tested with various types of multimodal and unimodal benchmark functions and its performance in terms of fitness accuracy is discussed. …”
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Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS
Published 2015“…The performances of the proposed algorithms are tested with various dimensions, fitness landscapes and complexities of several standard benchmark functions and they are statistically evaluated and compared with the original algorithm. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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14
Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan
Published 1997“…This bound enables us to prune the search tree efficiently. The algorithm will be implemented and tested in this project using C language. …”
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15
A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…The primary theoretical contribution is the TCP framework, which is applied in the software testing industry. TCP factors and a weighted fitness function are also used for test case optimisation. …”
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17
Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function
Published 2019“…However, the evaluation function used in the AI is developed based on historical traffic data. …”
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18
Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail
Published 2024“…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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19
Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment
Published 2021“…It is envisaged that this system and control algorithm can be very useful for the development of a mobile robot with extended functionality.…”
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance
Published 2023“…This algorithm can also be used for task scheduling. The proposed algorithm efficiently maps and achieves the objective function for server consolidation, optimising energy consumption, VM migrations, and server utilisation. …”
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