Multiobjective Optimization Method for Polymer Injection Molding Based on a Genetic Algorithm by Zhijun Yuan, Hui Wang, Xuebing Wei, Kui Yan, Cheng Gao

“…A mathematical model considering an objective and impact factors is developed using the response surface method. The optimal combination of the impact parameters is determined using a multiobjective genetic algorithm. …”
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Optimization of Communication Quality for Energy-Limited Inspection AAV: A Hybrid Algorithm by Wei Wang, Jiangling Cao, Dingcheng Yang, Hao He, Zhihai Xu

“…Numerical results show that the proposed algorithm is effective in optimizing the communication quality of the inspection AAV with limited energy, and its performance is improved by about 15%-50% compared with other benchmarks.…”
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Reducing hydrogen consumption in hybrid electric vehicles using aquila optimization algorithm by A.M. Nassef, H.E. Ghadbane, E.T. Sayed, H. Rezk

“…The aquila optimization algorithm is one of the most recent and efficient algorithms. …”
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Prediction and optimization of robot processing technology based on neural network and genetic algorithm by Fusen WU

“…Finally, the genetic algorithm was applied to optimize grinding process parameters with material removal rates as the indicator.ResultsThe grinding process parameters have significant effects on grinding forces, but the order of major and secondary effects of different parameters varies with grinding force components. …”
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Spike-RISC: Algorithm/ISA Co-Optimization for Efficient SNNs on RISC-V by Ipek Akdeniz, Sandy A. Wasif, Paul R. Genssler, Hussam Amrouch

“…This paper proposes Spike-RISC, a holistic algorithm/instruction set architecture (ISA) co-optimization for efficient SNN inference. …”
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Availability and uncertainty-aware optimal placement of capacitors and DSTATCOM in distribution network using improved exponential distribution optimizer by Abdulaziz Alanazi, Mohana Alanazi, Zulfiqar Ali Memon, Ahmed Bilal Awan, Mohamed Deriche

“…The decision variables include the installation location and the capacity of compensators, which are defined by a novel meta-heuristic algorithm termed the improved exponential distribution optimizer (IEDO). …”
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An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network by C. Vimalarani, R. Subramanian, S. N. Sivanandam

“…Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. …”
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Dynamic optimization of solar DG and shunt capacitor placement to mitigate the impact of EV charging stations on power distribution network by T. Yuvaraj, M. Thirumalai, T.D. Suresh, Sudhakar Babu Thanikanti, Mohammad Khishe

“…Simulation results confirm the superior performance of QRSMA in improving voltage profiles, reducing power losses, and achieving better computational efficiency compared to conventional optimization algorithms. …”
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Optimization of air conditioning mechanical ventilation using simulated annealing for enhanced energy efficiency and cost reduction by Enio Pedone Bandarra Filho, Gleyzer Martins, Muhammad Bilal Riaz, Sardar Muhammad Bilal, Oscar Saul Hernandez Mendonza

“…The methodology integrates principles of fluid mechanics with computational modeling to perform mass and pressure balances, combined with a simulated annealing algorithm for system optimization. The results demonstrate notable reductions in energy consumption, installation costs, and root mean square deviation of airflow rates from design targets. …”
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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Among the available methods, partial transmit sequence (PTS) is an efficient PAPR reduction method but can be computationally expensive while deter-mining optimal phase factors (OPFs). Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
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Innovative Hybrid Algorithm for Solving Vehicle Routing Problem with Time Window by A.M. Rahimi, B. Yadegari, M. Aboutalebi Esfahani

“…The proposed algorithm is suitable for transportation and logistics systems with limited customers and leads to cost reduction, improved delivery times, and increased service quality.…”
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An Improved LEACH Protocol for Optimizing Cluster Head Selection and In-cluster Selection by SHIBing, GAOZelin, SUNYueping, HUANJuan, SUNTao

“…This protocol initially employs the root mean square (RMS) of distance within the energy consumption model to determine the optimal number of cluster heads. …”
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GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation by Eman Mahmoud, Salem Alkhalaf, Tomonobu Senjyu, Masahiro Furukakoi, Ashraf Hemeida, Ghada Abozaid

“…However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresholds. This paper addresses this challenge by proposing a hybrid Genetic Algorithm-Archimedes Optimization Algorithm (GAAOA), further enhanced with a Lévy flight function (GAAOA-Lévy), to improve efficiency and accuracy in multilevel thresholding. …”
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Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

“…Such an integration acted as regular convolutional layers that subsequently substituted for the original layers to cut computational costs. Furthermore, we adopted the SIoU loss function, a modified version of CIoU, applied to the YOLOv8s model, demonstrating a substantial improvement in accuracy. …”
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An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem by Tao Zhang, Tiesong Hu, Yue Zheng, Xuning Guo

“…An improved particle swarm optimization (PSO) algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP). …”
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Load demand forecasting in air conditioning a rotor Hopfield neural network approach optimized by a new optimization algorithm by Mingguang Liu, Weibo Zhao, Ying Zhou, Mahdiyeh Eslami

“…The RHNN/FO-SOA method may contribute to improve energy performance and reduce costs in air conditioners, shown by the findings.…”
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Simultaneous Optimal Allocation of EVCSs and RESs Using an Improved Genetic Method by Majid Farjamipur, Hossein Lotfi, Mohammad Hassan Nikkhah

“…In this research, the improved nondominant sorting genetic algorithm is proposed to solve the problem, and the results of the proposed method are also compared with the conventional genetic and particle swarm optimization algorithms. …”
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Research on Optimal Site Selection for Offshore Wind Farms Substation by Yuan YANG, Xiang Tang, Yanli XIN

“…Site selection of offshore substation plays a vital role for wind farm investment cost. This paper presents a method for optimal substation site selection for offshore wind farms substation. …”
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Adaptive Grasp Pose Optimization for Robotic Arms Using Low-Cost Depth Sensors in Complex Environments by Aiguo Chen, Xuanfeng Li, Kerui Cen, Chitin Hon

“…Unlike traditional deep learning methods, which suffer from high data dependency and inefficiency with low-precision point clouds, the proposed approach uses ellipsoidal modeling to overcome these issues. The algorithm segments the target and then applies a three-stage optimization to refine the grasping path. …”
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Healthcare Prediction Using Novel Machine Learning Methods and Metaheuristic Algorithm by Yazdan Ashgevari, Behrouz Alefy, Faranak Kazemi

“…Four models ETSA, ETCH, SVSA, and SVCH were developed in this study by integrating the ETC and SVC models with two optimization algorithms the CHS and SAO. Upon analyzing the performance of these models, it was found that the ETSA model had a high precision of 0.806 in normal conditions.…”
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