Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

“… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
Get full text

Research on 3D Path Optimization for an Inspection Micro-Robot in Oil-Immersed Transformers Based on a Hybrid Algorithm by Junji Feng, Xinghua Liu, Hongxin Ji, Chun He, Liqing Liu

“…Once the optimal node sequence is determined, detailed path planning between adjacent points is executed through a synergistic combination of the A algorithm*, Rapidly exploring Random Tree (RRT), and Particle Swarm Optimization (PSO). …”
Get full text

Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

“…The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
Get full text

An improved multi-objective particle swarm optimization algorithm for the design of foundation pit of rail transit upper cover project by Jinyan Shao, Yuan Lu, Yi Sun, Lei Zhao

“…The algorithm retains the basic convergence mechanism of particle swarm optimization (PSO) as its core, while innovatively combining the fast non-dominated sorting technique to effectively evaluate and approximate the Pareto optimal solution set. …”
Get full text

Enhanced futures price-spread forecasting based on an attention-driven optimized LSTM network: integrating an improved grey wolf optimizer algorithm for enhanced accuracy by Yongli Tang, Zhenlun Gao, Zhongqi Cai, Jinxia Yu, Panke Qin

Get full text

Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm by Sydney Mutale, Yong Wang, De Tian

“…This study introduces a novel approach for minimizing assembly errors in wind turbine gearboxes using a hybrid optimization algorithm, Particle Swarm-Bacteria Foraging Optimization (PSBFO). …”
Get full text

Optimization of the parameters of truss beams with two posts by A. K. Yusupov, H. M. Musеlеmov, T. O. Ustarhanov

“…Using the example of numerical calculations, a decrease in the calculated bending moment by 14% compared to truss beams without optimization is shown.Conclusion. The proposed method and algorithm testify to the efficiency and rationality of the obtained optimal parameter of the structure as a whole.…”
Get full text

Quantum Snowflake Algorithm (QSA): A Snowflake-Inspired, Quantum-Driven Metaheuristic for Large-Scale Continuous and Discrete Optimization with Application to the Traveling Salesma... by Zeki Oralhan, Burcu Oralhan

“…The Quantum Snowflake Algorithm (QSA) is a novel metaheuristic for both continuous and discrete optimization problems, combining collision-based diversity, quantum-inspired tunneling, superposition-based partial solution sharing, and local refinement steps. …”
Get full text

Hybrid MPPT control using hybrid pelican optimization algorithm with perturb and observe for PV connected grid by Burhan U. Din Abdullah, Suman Lata Dhar, Shiva Pujan Jaiswal, Muhammad Majid Gulzar, Muhammad Majid Gulzar, Mohammad Alqahtani, Muhammad Khalid, Muhammad Khalid

“…Traditional Maximum Power Point Tracking (MPPT) methods struggle to adapt accurately to these dynamic environmental conditions. While Artificial Intelligence (AI) and optimization techniques show promise, their implementation complexity and longer attainment times for Maximum Power Point (MPP) hinder widespread adoption.MethodThis paper proposes a hybrid MPPT technique that integrates the Pelican Optimization algorithm (POA) with the Perturb and Observe algorithm (P&O) for a grid-connected photovoltaic system (PV). …”
Get full text

A Unified Multi-Target Clever Eye Algorithm: Analytical Solutions and Application by Lei Wang, Xiurui Geng, Luyan Ji

“…The clever eye (CE) algorithm has been introduced for target detection in remote sensing image processing. …”
Get full text

Novel distance-fitness learning scheme for ameliorating metaheuristic optimization by Emre Çelik, Essam H. Houssein, Mahmoud Abdel-Salam, Diego Oliva, Ghanshyam G. Tejani, Nihat Öztürk, Sunil Kumar Sharma, Mohammed Baljon

Get full text

Improved optimization based on parrot’s chaotic optimizer for solving complex problems in engineering and medical image segmentation by Adil Sayyouri, Ahmed Bencherqui, Hanaa Mansouri, Hicham Karmouni, Hassane Moustabchir, Mhamed Sayyouri, Abderrahim Bourkane, Abdeljabbar Cherkaoui, S. S. Askar, Mohamed Abouhawwash

“…Abstract Metaheuristics, which are general-purpose algorithms, are commonly used to solve complex optimization problems. …”
Get full text

Sensitivity analysis of activity scheduling parameters with a parameter optimization framework by Matheus Moro Zamprogno, Domokos Esztergár-Kiss

“…In this research, the activity chain optimization algorithm is applied, which requires high computational efforts. …”
Get full text

Edge detection of aerial images using artificial bee colony algorithm by Nurdan Akhan Baykan, Elif Deniz Yelmenoglu

“…In this paper, aerial images are used for edge information extraction by using Artificial Bee Colony (ABC) Optimization Algorithm. Procedures were performed on gray scale aerial images which are taken from RADIUS/DARPA-IU Fort Hood database. …”
Get full text

Vehicle Attitude Control of Magnetorheological Semi-Active Suspension Based on Multi-Objective Intelligent Optimization Algorithm by Kailiang Han, Yiming Hu, Dequan Zeng, Yinquan Yu, Lei Xiao, Jinwen Yang, Weidong Liu, Letian Gao

“…A multi-objective intelligent optimization algorithm-based attitude control strategy for magnetorheological semi-active suspension is proposed to address the vehicle attitude imbalance generated during steering and braking. …”
Get full text

A PROBLEM OF CUTTING OFF THE LAMINATED SEMIS TYPE PLATE by Florin Ciofu

“…With this purpose there are algorithms of optimizing for positioning the parts following to be cut off from a row plate. …”
Get full text

3D Deployment Optimization of Wireless Sensor Networks for Heterogeneous Functional Nodes by Zean Lu, Chengqun Wang, Peng Wang, Weiqiang Xu

“…The algorithm is compared with the original SBOA, Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Northern Goshawk Optimization (NGO). …”
Get full text

Energy management strategy for methanol hybrid commercial vehicles based on improved dung beetle algorithm optimization. by Zhihao Li, Ping Xiao, Jiabao Pan, Wenjun Pei, Aoning Lv

“…In order to solve the problem of poor adaptability and robustness of the rule-based energy management strategy (EMS) in hybrid commercial vehicles, leading to suboptimal vehicle economy, this paper proposes an improved dung beetle algorithm (DBO) optimized multi-fuzzy control EMS. …”
Get full text

Effect of the Sampling of a Dataset in the Hyperparameter Optimization Phase over the Efficiency of a Machine Learning Algorithm by Noemí DeCastro-García, Ángel Luis Muñoz Castañeda, David Escudero García, Miguel V. Carriegos

“…It is a laborious task that usually requires deep knowledge of the hyperparameter optimizations methods and the Machine Learning algorithms. …”
Get full text

Enhanced vehicle routing for medical waste management via hybrid deep reinforcement learning and optimization algorithms by Norhan Khallaf, Osama Abd-El Rouf, Abeer D. Algarni, Mohy Hadhoud, Ahmed Kafafy

“…Despite this trade-off, the algorithm’s ability to minimize fleet size while fully utilizing vehicle capacity makes it the optimal choice in scenarios where these factors are critical. …”
Get full text