Multiobjective Cognitive Cooperative Jamming Decision-Making Method Based on Tabu Search-Artificial Bee Colony Algorithm by Fang Ye, Fei Che, Lipeng Gao

“…In addition, the conventional artificial bee colony algorithm takes too many iterations, and the improved ant colony (IAC) algorithm is easy to fall into the local optimal solution. …”
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Improved particle swarm optimization for fractional order PID control design in robotic manipulator system: A performance analysis by Gamil Ahmed, Ahmed Eltayeb, Nezar M. Alyazidi, Imil Hamda Imran, Tarek Sheltami, Sami El-Ferik

“…The controller has undergone refinement and enhancement using state-of-the-art particle swarm optimization (PSO) techniques incorporating a cost function and a representative bio-inspired algorithm. …”
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Integrated Approach to Optimizing Selection and Placement of Water Pipeline Condition Monitoring Technologies by Diego Calderon, Mohammad Najafi

“…This article introduces a unified framework and methods for optimally selecting condition monitoring technologies while locating their deployment at the most vulnerable pipe segments. …”
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Evaluating the Efficiency of Gray Wolf Optimization and Colonial Competition Algorithm in Load Balancing of Distributed Systems by Asghar Molaei-Yeznabad, Amirhossein Dehghani

“…Recent years have seen the development of numerous resource allocation algorithms aimed at reducing costs and energy consumption in distributed systems. …”
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Performance optimization of electrical equipment in high-altitude photovoltaic power stations based on PSO–MOEAD algorithm by Zhijun Xiao

“…To reduce energy consumption and operation and maintenance costs, a hybrid algorithm based on particle swarm optimization and multi-objective evolutionary decomposition algorithm is proposed in this study. …”
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Risk assessment and hybrid algorithm transportation path optimization model for road transport of dangerous goods by Qiankun Jiang, Haiyan Wang

“…After calculating the weights of each indicator, this study improves the parameters of the particle swarm algorithm using the aggregation and foraging behavior of artificial fish, and uses the improved algorithm to solve the optimal solution for the cost of dangerous goods road transportation. …”
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Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
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Tabu Genetic Cat Swarm Algorithm Analysis of Optimization Arrangement on Mistuned Blades Based on CUDA by Yi Cai, Junjie Gu, Honggang Pan, Hongyuan Zhang, Tianyu Zhao

“…Tabu genetic cat swarm optimization algorithm is proposed for optimization arrangement on mistuned blades. …”
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Research of UAV 3D path planning based on improved Dwarf mongoose algorithm with multiple strategies by Lixin Mu, Wenhui Liu, Haocheng Wang, Yu Zhang

“…To enhance UAV adaptability in such environments, improve rapid and efficient path planning capabilities, and reduce operational costs, this paper proposes a 3D UAV path planning algorithm based on an improved Dwarf Mongoose Optimization (DMO) algorithm enhanced with multiple strategies. …”
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Magnetic targets positioning method based on multi-strategy improved Grey Wolf optimizer by Binjie Lu, Zongji Li, Xiaobing Zhang

“…Therefore, a Multi-Strategy Improved Grey Wolf Optimizer (MSIGWO) algorithm has been proposed to enhance the accuracy of magnetic target state estimation. …”
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Improved Multiobjective Genetic Algorithm for Partitioning Distributed Photovoltaic Clusters: Balancing Spatial Distance and Power Similarity by Yansen Chen, Kai Cheng, Zhuohuan Li, Shixian Pan, Xudong Hu

“…This cluster segmentation algorithm significantly reduces the complexity and investment cost of the prediction system.…”
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An Optimization Model for Production Scheduling in Parallel Machine Systems by Leting Zu, Wenzhu Liao, Xiaoxia Yang

“…A well-designed production scheduling scheme can significantly enhance manufacturing efficiency and reduce enterprise costs. This paper presents a tailored optimization model designed to address a more complex production scheduling problem that incorporates parallel machines and preventive maintenance. …”
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A design method of composite pixel-like antenna based on improved bald eagle search algorithm by WANG Yongqiang, LIU Bingqi, ZHU Bolin

“…This method not only retains the good convergence of the original algorithm, but also partially improves the global search ability. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…This aimed to optimize the Light Gradient-Boosting Machine (LightGBM) algorithm to enhance its performance and accuracy in the early detection of CHD, providing a reliable, cost-effective, and non-invasive diagnostic tool. …”
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Study on optimization of Al6061 sphere surface roughness in diamond turning based on central composite design model and grey wolf optimizer algorithms by Le Thanh Binh, Duong Xuan Bien, Ngo Viet Hung, Chu Anh My, Hoang Nghia Duc, Nguyen Kim Hung, Bui Kim Hoa

“…This paper presents optimization results of the Al6061 surface roughness in turning ultra-precision based on the central composite design method (CCD) and the grey wolf optimization algorithm (GWO). …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. …”
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

“…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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Sequential Routing-Loading Algorithm for Optimizing One-Door Container Closed-Loop Logistics Operations by Paulina Kus Ariningsih, Titi Iswari, Kevin Djoenneady Poetra, Yoon Mac Kinley Aritonang

“…The improvement algorithm is tested in big data set with the input of the vehicle routing problem with time windows (VRP-TW) using the solution optimization of the Simulated Annealing process with restart point procedure (SA-R) for the routing optimization and Genetic Algorithm (GA) to optimize the container loading algorithm. …”
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Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network by Nandita Goyal, Munesh Chandra Trivedi

“…The proposed system makes a comparison of models with and without feature selection algorithms before applying the data to CNN. A comparison of different metaheuristics algorithms- Particle Swarm Optimization, Shuffled Frog Leap Optimization and Fire fly algorithm for feature optimization is done based on convergence rate and efficiency.…”
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