An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan by Ghulam Abbas, Arshad Ali, Faizan Rashid, Naveed Ashraf, Zohaib Mushtaq, Muhammad Zubair

“…In this research, we have ameliorated the performance of the recently-introduced novel energy pattern factor method (NEPFM) via a direct search algorithm, i.e., simplex search algorithm (SSA). We designate the resulting algorithm as NEPFM-SSA as it took NEPFM’s Weibull distribution parameters as an initial guess and retuned them with the help of the simplex search algorithm to get updated Weibull distribution parameters, which ensure better fitting characteristics. …”
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Individual health passport storage, sharing and verification scheme based on blockchain by GAO Hancheng, JI Haoyu, GAO Chenhao, HUANG Haiping

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Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization by P. Nirmala, G. Ramkumar, Satyajeet Sahoo, G. Anitha, S. Ramesh, S. Agnes Shifani, Agegnehu Shara Shata

“…PSO-GA (Particle Swarm Optimization and Genetic Algorithm) is utilized to analyze the performance. …”
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Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue by Chongde CHEN, Qiang GUO, Ziqiu SONG, Yang HU

“…The wind power offset was decomposed by a Butterworth low-pass filter, and the low-frequency and high-frequency components were used as the reference power of lithium battery energy storage and flywheel energy storage, respectively. In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. …”
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Research on optimization of C4 repair operation of Harmony electric locomotive based on preventive maintenance. by Yihan Liu, Jieping Wu, Qiaoyu Wu

“…Under the premise of ensuring locomotive operational safety, it effectively saves costs, reduces maintenance downtime and achieves the objective of improving the quality of C4 repairs.…”
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Hybrid Hunger Games Search optimization using a neural networks approach applied to UAVs by Nadia Samantha Zuñiga-Peña, Salatiel Garcia-Nava, Norberto Hernandez-Romero, Juan Carlos Seck-Touh-Mora

“…Optimization methods like population-based algorithms are valuable when applied to multidimensional and nonlinear problems. …”
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Optimization Model of Express–Local Train Schedules Under Cross-Line Operation of Suburban Railway by Jingyi Zhu, Xin Guo, Jianju Pan

“…Comparative analysis shows that the proposed hybrid operation mode reduces total passenger travel cost by 6% and improves the cost efficiency ratio by 13% compared to independent operations. …”
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Optimizing Scheduled Virtual Machine Requests Placement in Cloud Environments: A Tabu Search Approach by Mohamed Koubàa, Abdullah S. Karar, Faouzi Bahloul

“…This advancement highlights the TS algorithm’s potential to deliver substantial scalability and optimization benefits, particularly for high-demand scenarios, albeit with a necessary consideration for computational cost.…”
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Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment by Jing Zhang, Jingjing Liu, Zhong Wan

“…For this complicated polymorphic uncertain optimization model, a unified compromising approach is proposed to hedge the uncertainty of this model such that some powerful optimization algorithms can be applied to make an optimal recycling plan. …”
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Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management by Vikram Pasupuleti, Bharadwaj Thuraka, Chandra Shikhi Kodete, Saiteja Malisetty

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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…This paper presents an enhanced hybrid particle swarm optimization (EHPSO) algorithm that incorporates a spatial position encoding (SPE) strategy to optimize coverage while dynamically adjusting the number of sensors deployed in WSNs. …”
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Optimized Software Implementation of Keccak, Kyber, and Dilithium on RV{32,64}IM{B}{V} by Jipeng Zhang, Yuxing Yan, Junhao Huang, Çetin Kaya Koç

“… With the standardization of NIST post-quantum cryptographic (PQC) schemes, optimizing these PQC schemes across various platforms presents significant research value. …”
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Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy by Haiteng Han, Xiangchen Jiang, Yang Cao, Xuanyao Luo, Sheng Liu, Bei Yang

“…Case study analyses demonstrate that, compared to single-resource configurations, the proposed coordinated planning of multiple flexibility resources can significantly reduce the total system cost and markedly improve system resilience under fault conditions.…”
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An adaptive differential evolution algorithm to solve the multi-compartment vehicle routing problem: A case of cold chain transportation problem by Supaporn Sankul, Naratip Supattananon, Raknoi Akararungruangkul, Narong Wichapa

“…To improve the original DE algorithm, the proposed algorithm increases the number of mutation equations from one to four. …”
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Optimization of Urban Rail Transit Train Stock Utilization under Re-coupling Operation Mode by DENG Chengyuan, LU Jinsheng, ZHU Changfeng, SUN Yuanguang, MA Bin

“…In the case study of a certain urban rail transit line with significant imbalance of passenger flow in different periods, the feasibility and rationality of the above optimized model are verified. ［Result & Conclusion］ The optimized train stock utilization scheme of urban rail transit under the re-coupling operation mode can reasonably optimize the connection between different marshalling train trips and reduce the operation costs for enterprises.…”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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Forecasting the vapor pressure deficit in vertical farming facilities aiming to provide optimal indoor conditions by Carlos Alejandro Perez Garcia, Dafni Despoina Avgoustaki, Enrica Santolini, Daniele Torreggiani, Thomas Bartzanas, Patrizia Tassinari, Marco Bovo

“…The model, demonstrating satisfactory performance in predicting VPD, enables optimization of indoor growth conditions, thereby improving resources use efficiency and minimizing operational costs. …”
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Deep reinforcement learning-based resource joint optimization for millimeter-wave massive MIMO systems by LIU Qingli, LI Xiaoyu, LI Rui

“…Experimental results show that the proposed joint optimization method significantly improves the throughput and energy efficiency of the system compared with the single-stage all-digital precoding and hybrid precoding equal resource allocation methods and the particle swarm optimization-based resource allocation algorithm.…”
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Integration of Regression-Based Guidance Ant for Enhanced Exploration and Convergence in Ant Colony Optimization (ACO) by Desi W. Sari, Suci Dwijayanti, Bhakti Y. Suprapto

“…To address these limitations, this research incorporates a linear regression line as a directional guide for ants, helping them navigate toward the optimal path more efficiently. This paper presents an improved Ant Colony Optimization (I-ACO) algorithm by integrating regression-based guidance to enhance both exploration and convergence. …”
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A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction by Gao Wang, Shuang Xu, Zixu Chen, Youzhu Li

“…This study proposes a hybrid forecasting model integrating variational mode decomposition (VMD), the Fruit Fly Optimization Algorithm (FOA), and a gated recurrent unit (GRU). …”
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