OPTIMISATION OF THE MACHINING PROCESS USING GENETIC ALGORITHM by Nadežda ČUBOŇOVÁ, Tomáš DODOK, Zuzana SÁGOVÁ

“…This paper deals with genetic algorithms as an optimisation method and its use for optimisation of the machining process in the CAM system. …”
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On the Effectiveness of Optimisation Algorithms for Hydrodynamic Lubrication Problems by František Kocman, Pavel Novotný

“…While the PSWM algorithm also reliably found the global minimum, it exhibited lower speed in the defined problems. …”
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Swarm Behaviour Optimisation Methods Based on an Original Algorithm by Krzysztof FALKOWSKI, Michał DUDA

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Microservice combination optimisation based on improved gray wolf algorithm by Jingjing Hu, Xiaojun Xu, Jin Hao, Xiuqi Yang, Kefan Qiu, Yuanzhang Li

“…The experimental results verify that the error rate of the method is only 0.528% on the non-functional combination optimisation problem, and the computational efficiency of the algorithm increases by 97.29% when the complexity of the problem search space increases, while CGWO improves 65.97% and 81.25% respectively in the accuracy of optimisation compared to the prototype of the algorithm (GWO), and has a stable optimisation performance, aspect. …”
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An Interleaved Artificial Bee Colony algorithm for dynamic optimisation problems by Salwani Abdullah, Shams K. Nseef, Ayad Turky

“…This requires an optimisation algorithm that should be able to monitor the movement of the optimal point and the changes in the landscape solutions. …”
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Comparing variable neighbourhood search algorithms for the direct aperture optimisation in radiotherapy by Mauricio Moyano, Keiny Meza-Vasquez, Gonzalo Tello-Valenzuela, Nicolle Ojeda-Ortega, Carolina Lagos, Guillermo Cabrera-Guerrero

“…This approach allows for a more thorough solution for space exploration while maintaining computational efficiency. The rVNS, unlike traditional VNS algorithms, does not require any transition rule, as it integrates a set of predefined neighbourhood moves at each iteration. …”
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Exploration-Driven Genetic Algorithms for Hyperparameter Optimisation in Deep Reinforcement Learning by Bartłomiej Brzęk, Barbara Probierz, Jan Kozak

“…This paper investigates the application of genetic algorithms (GAs) for hyperparameter optimisation in deep reinforcement learning (RL), focusing on the Deep Q-Learning (DQN) algorithm. …”
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An Automated Structural Optimisation Methodology for Scissor Structures Using a Genetic Algorithm by Aushim Koumar, Tine Tysmans, Rajan Filomeno Coelho, Niels De Temmerman

“…Compared to other optimisation methods, genetic algorithms are more robust and efficient when dealing with multiobjective optimisation problems and provide a better view of the search space while reducing the chance to be stuck in a local minimum. …”
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Smooth Optimised A*-Guided DWA for Mobile Robot Path Planning by Liling Cao, Lei Tang, Shouqi Cao, Qing Sun, Guofeng Zhou

“…To address these issues, a smoothing optimised A*-guided DWA fusion algorithm (SOA-DWA) is proposed in this paper. …”
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Optimising islanded AC microgrid control: A hierarchical approach with FCS-VMPC and consensus algorithm by Zawar Khan, Muhammad Aamir, Rizwanullah Khan, Mohd Fairouz Mohd Yousof

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Optimisation of Ensemble Learning Algorithms for Geotechnical Applications: A Mathematical Approach to Relative Density Prediction by Mahdy Khari, Ali Dehghanbanadaki, Danial Jahed Armaghani, Manoj Khandelwal

“…A novel approach to optimise ensemble learning algorithms is presented, with a focus placed on the mathematical foundations of these methods. …”
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Analysis of Electromagnetic Propagation from MHz to THz with a Memory-Optimised CPML-FDTD Algorithm by A. Rodríguez-Sánchez, C. Couder-Castañeda, J. J. Hernández-Gómez, I. Medina, S. Peña-Ruiz, J. Sosa-Pedroza, M. A. Enciso-Aguilar

“…In this paper, we present an optimised FDTD-CPML algorithm, focused in saving memory while increasing the performance of the algorithm. …”
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Kinematic analysis and optimisation of a gantry spraying robot for ship blocks by Jiangmin Xu, Jinhao Liu, Xuwen Jing, Honggen Zhou, Xiaocai Hu, Jianbo Ji, Zhenchun Han

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Optimising Warehouse Order Picking: Real Case Application in the Shoe Manufacturing Industry by Rodrigo Furlan de Assis, William de Paula Ferreira, Alexandre Frias Faria, Luis Antonio Santa-Eulalia, Mustapha Ouhimmou, Ali Gharbi

“…To address this challenge, we present the Genetic Route Optimisation algorithm for optimising order-picking routes. …”
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Enhanced optimisation of MPLS network traffic using a novel adjustable Bat algorithm with loudness optimizer by Mohsin Masood, Mohamed Mostafa Fouad, Rashid Kamal, Khursheed Aurangzeb, Sheraz Aslam, Zahid Ullah, Ivan Glesk

“…This paper addresses this challenge by transforming the path computation into an optimisation task. The Bat Algorithm, a popular meta-heuristic approach, is frequently employed for solving such optimisation problems. …”
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Balancing accuracy and convergence rate: a hybrid optimisation algorithm for parameter identification of unmanned marine vehicles by Zheng Li, Caoyang Yu, Yiming Zhong, Yuanju Cao, Xianbo Xiang, Lian Lian

“…In this paper, a novel and well-balanced hybrid optimisation algorithm called NMA is proposed for parameter identification of a coupled three-degree-of-freedom unmanned marine vehicle in the presence of measurement noise. …”
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Optimal design of hollow conductor for high‐speed synchronous motor exploiting adaptive‐sampling radial basis function algorithm by Ruiye Li, Peng Cheng, Hai Lan

“…The ASRBF algorithm adaptively adds sample points by estimating expected improvements at prediction points, enabling the surrogate model to rapidly approximate the global optimum while significantly reducing function evaluations. …”
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Two New Bio-Inspired Particle Swarm Optimisation Algorithms for Single-Objective Continuous Variable Problems Based on Eavesdropping and Altruistic Animal Behaviours by Fevzi Tugrul Varna, Phil Husbands

“…On the CEC13 test suite, across all dimensions, both BEPSO and AHPSO performed statistically significantly better than 10 of the 15 comparator algorithms, while none of the remaining 5 algorithms performed significantly better than either BEPSO or AHPSO. …”
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Leveraging genetic algorithms and neural networks for stiffness and weight optimisation of an unmanned aerial vehicle (UAV) support arm by Iuri H. Müller, José Humberto S. Almeida Jr, Sandro C. Amico, Maikson L.P. Tonatto

“…This study proposes a multi-objective optimisation approach that integrates the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) with an Artificial Neural Network (ANN) to optimise the design of a UAV support arm. …”
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A synergic quantum particle swarm optimisation for constrained combinatorial test generation by Xu Guo, Xiaoyu Song, Jian‐tao Zhou

“…Under this scenario, constrained covering array generation (CCAG), a vital combinatorial optimisation issue targeted with constructing a test suite of minimal size while properly addressing constraints, remains challenging in CT. …”
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