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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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2
Optimization of multi-holes drilling path using particle swarm optimization
Published 2022“…The performance of PSO was then compared with other meta-heuristic algorithms, including Genetic Algorithm (GA) and Ant Colony Optimisation (ACO), Whale Optimisation Algorithm (WOA), Ant Lion Optimiser (ALO), Dragonfly Algorithm (DA), Grasshopper Optimisation Algorithm (GOA), Moth Flame Optimisation (MFO) and Sine Cosine Algorithm (SCA). …”
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3
Optimised crossover genetic algorithm for capacitated vehicle routing problem
Published 2012“…The proposed algorithm uses an optimised crossover operator designed by a complete undirected bipartite graph to find an optimal set of delivery routes satisfying the requirements and giving minimal total cost. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduction.
Published 2023“…Having those said, this study proposes BESS optimisation to reduce the total system losses using modified Whale Optimisation Algorithm (WOA) with high exploration and exploitation features. …”
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ENGINEERING DESIGN WITH PSO ALGORITHM
Published 2019“…This dissertation will demonstrate the ability of PSO Algorithm in improving design areas by the use of recommendation system that helps engineering designers to visualise an optimal design.…”
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6
Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…This research aimed to determine the optimal feeding strategy for fed-batch baker’s yeast fermentation process using the deep reinforcement learning algorithm in maximising the final production of yeast, while minimising the undesired ethanol formation. …”
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7
Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…The proposed algorithm is evaluated using tasks scheduling in the scheduling load simulator and validated using statistical modeling. …”
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Multi-objective optimisation of assembly line balancing type-e problem with resource constraints
Published 2016“…In this research, a Genetic-based Algorithm was used as an optimisation approach. …”
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10
Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Published 1993“…The double iterative loop structures of the proposed algorithms use the real process measurement within the outer loops while the inner loops involve model based computation only. …”
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Bee colony optimisation of the travelling salesman problem in light rail systems
Published 2019“…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024“…The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…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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14
Breast cancer diagnosis through an optimization-driven multispectral gamma correction (ODMGC)
Published 2024“…The algorithm was successfully implemented in MATLAB 2020a, and the classifier was developed in Jupyter Notebook using Python. …”
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Two-wheeled LEGO EV3 Robot stabilisation control using fuzzy logic based PSO algorithm
Published 2019“…The fuzzy logic controller is used to stabilise this robot with Particle Swarm Optimization algorithm for optimum performance of the system. …”
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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 then used to optimise parameters of the ARX structure. …”
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Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan
Published 1997“…Searching for possible abutment between the transistor pairs are modelled as a bipartite graph. A depth - first search algorithm is used to search for optimal chaining. …”
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18
Application of a primal-dual interior point algorithm using exact second order information with a novel non-monotone line search method to generally constrained minimax optimizatio...
Published 2008“…This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation
Published 2024“…Unlike benchmark algorithms that rely on static VM selection or post-hoc relocation of cloudlets, the EDLB algorithm dynamically identifies optimal cloudlet placement in real-time. …”
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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“…This paper presents investigations into the development of an interval type-2 fuzzy logic control (IT2FLC) mechanism integrated with particle swarm optimization and spiral dynamic algorithm. The particle swarm optimization and spiral dynamic algorithm are used for enhanced performance of the IT2FLC by finding optimised values for input and output controller gains and parameter values of IT2FLC membership function as comparison purpose in order to identify better solution for the system. …”
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