Presenting a multi-objective decision-making model for cost-time trade-off considering the time value of money and solving it using particle swarm optimization by Mohammadreza Shahriari

“…This model assists project managers in gaining better insight into cost-time impacts, optimizing resource allocation, and ultimately improving project performance by reducing delays.…”
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Dynamic reconfiguration of the distribution systems with Load Duration Curve (LDC) model for reducing the losses and improving the voltage profile by Sana Sadeghi, Alireza Jahangiri, Ahmad Ghaderi Shamim

“…Simulations were conducted on the well-established IEEE 33-bus test system, employing MATLAB software in conjunction with a genetic algorithm to minimize losses and optimize voltage profiles. …”
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A Feasibility Study of a Virtual Power Line Device to Improve Hosting Capacity in Renewable Energy Sources by Seong-Eun Rho, Sung-Moon Choi, Joong-Seon Lee, Hyun-Sang You, Seung-Ho Lee, Dae-Seok Rho

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An application of Arctic puffin optimization algorithm of a production model for selling price and green level dependent demand with interval uncertainty by Hachen Ali, Md. Al-Amin Khan, Ali Akbar Shaikh, Adel Fahad Alrasheedi, Seyedali Mirjalili

“…Furthermore, seven other algorithms (Dandelion Optimizer (DO), Grey wolf optimizer (GWO), The whale optimization algorithm (WOA), Artificial electric field algorithm (AEFA), Harris hawks optimization (HHO), Multi-verse optimizer (MVO) and Slime mould algorithm (SMA)) are used to compare the obtained solution from APO. …”
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Multi-Stage Coordinated Planning Method for Transmission Network and Energy Storage Considering Carbon Trading Cost by Qiang LI, Yao WANG, Yingying HU, Xiaoming ZHENG, Linna ZHANG, Yongming JING

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Effects of off-design performances and multiple market carbon trading mechanism on integrated energy systems with waste incineration power units by Jing Liu, Tong Zhao, Haolin Sui

“…Furthermore, to analyze effects of off-design performances and MMCTM on the electricity-gas-heating-cooling IES, five case studies have been conducted on a typical electricity-gas-heating-cooling IES and the improved slime mould algorithm (ISMA) were adopted. …”
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Enhancing Lidar-Based 3D Classification Through an Improved Deep Learning Framework With Residual Connections by Shih-Lin Lin, Jun-Yi Wu

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Mathematical Formulation of Intelligent Management Algorithms for Isolated Microgrids: A Pareto-Based Critical Approach by Vitor dos Santos Batista, Thiago Mota Soares, Maria Emília de Lima Tostes, Ubiratan Holanda Bezerra, Hugo Gonçalves Lott

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An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

“…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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The Hub Location and Flow Assignment Problem in the Intermodal Express Network of High-Speed Railways and Highways by Xiaoting Shang, Zhenghang Wang, Xin Cheng, Xiaoyun Tian

“…Owing to the NP-hard computational complexity, an improved genetic algorithm with local search is designed by combining the genetic operators and two optimization strategies to solve the problem effectively. …”
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Research on the Gas Emission Quantity Prediction Model of Improved Artificial Bee Colony Algorithm and Weighted Least Squares Support Vector Machine (IABC-WLSSVM) by Lei Wang, Jinghang Li, Wenbo Zhang, Yu Li

“…At the same time, the improved artificial bee colony algorithm is used to optimize the kernel width σ and regularization parameter λ of WLSSVM, which improves the prediction accuracy and convergence rate of WLSSVM. …”
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Optimal Computation Offloading Decisions Based on System Utility and Cost Balance by Bingxue Zhang, Xisheng Li, Jia You

“…By calculating the full load rate of edge server clusters, we describe and evaluate the operational efficiency of the system, aiming to design a computation offloading decision scheme that not only reduces costs, but also enhances system utility. Based on the new evaluation model, an objective function is constructed to minimize the system’s cost-utility ratio, and an improved particle swarm optimization algorithm with enhanced search capabilities is proposed to solve it by designing a computation offloading strategy. …”
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Illustration Design Model with Clustering Optimization Genetic Algorithm by Jing Liu, Qixing Chen, Xiaoying Tian

“…This paper proposes an illustration art design model based on operator and clustering optimization genetic algorithm. First, during the operation of the genetic algorithm, the values of the crossover probability and the mutation probability are dynamically adjusted according to the characteristics of the population to improve the search efficiency of the algorithm, then the k-medoids algorithm is introduced to optimize the clustering of the genetic algorithm, and a cost function is used to carry out and evaluate the quality of clustering to optimize the complexity of the original algorithm. …”
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Adaptive crayfish optimization algorithm for multi-objective scheduling optimization in distributed production workshops by Xin Yang, Xiaoying Yang, Jinhao Du

“…Furthermore, an improved crowding distance calculation enhances the algorithm’s performance in multi-objective optimization by improving solution distribution. …”
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Improved A* Algorithm Based on Artificial Potential Field Method for Global Path Planning of Unmanned Surface Vessels in Complex Environments by Shuxuan Liu, Zhijia Qian, Sunwei Jiang, Quanming Miao

“…In the improved A* algorithm, the search direction was first optimized, simplifying the traditional eight direction search to a “target point attracts four directions” search, significantly reducing the ineffective expansion nodes of the traditional algorithm, reducing algorithm running time, and improving search efficiency; Secondly, on the basis of improving the cost function, the idea of artificial potential field algorithm is integrated, and the repulsive function is introduced. …”
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An adaptive prediction method for ultra-short-term generation power of power system based on the improved long- and short-term memory network of sparrow algorithm by Peipei Yang, Zhidong Chen, Wen Tang, Zongyang Liu, Bingrui He

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A Fast Recognition Method for Dynamic Blasting Fragmentation Based on YOLOv8 and Binocular Vision by Ming Tao, Ziheng Xiao, Yulong Liu, Lei Huang, Gongliang Xiang, Yuanquan Xu

“…As the primary method used in open-pit mining, blasting has a direct impact on the efficiency and cost of subsequent operations. Therefore, dynamic identification of rock fragment size after blasting is essential for evaluating blasting quality and optimizing mining plans. …”
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Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering by V. I. Koshelev, Ngoc Hieu Trinh

“…Separate optimization of weighting processing for each frequency channel can significantly improve the average efficiency characteristics of a multichannel Doppler filter and eliminate all the shortcomings of the classical and modified FFT algorithms when processing non-equidistant pulse sequences. …”
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Logarithmic mean optimization a metaheuristic algorithm for global and case specific energy optimization by Idriss Dagal, Ambe Harrison, Wulfran Fendzi Mbasso, Fritz Nguemo Kemdoum, Mohammad Khishe, Pradeep Jangir, Aseel Smerat, Saad F. Al-Gahtani, Z. M.S. Elbarbary, Emmanuel Fendzi Donfack, Hassan Abouobaida

“…LMO achieved the best solution on 19 out of 23 benchmark functions, significantly outperforming all comparison algorithms. It demonstrated a mean improvement of 83% in convergence time and up to 95% better accuracy in optimal values over competitors. …”
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Variance Reduction Optimization Algorithm Based on Random Sampling by GUO Zhenhua, YAN Ruidong, QIU Zhiyong, ZHAO Yaqian, LI Rengang

“…The main feature of the algorithm including an inner and outer double loop structure is designed: the outer loop structure uses mini-batch random samples to calculate the gradient, approximating the full gradient and reducing the gradient calculation cost; the inner loop structure also uses mini-batch random samples to calculate the gradient and replace the single sample random gradient, improving convergence stability of the algorithm. …”
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