Advanced Sales Route Optimization Through Enhanced Genetic Algorithms and Real-Time Navigation Systems by Wilmer Clemente Cunuhay Cuchipe, Johnny Bajaña Zajia, Byron Oviedo, Cristian Zambrano-Vega

“…Although GAAM-TS incurs higher computational costs, it is best suited for offline or batch optimization scenarios, whereas GA-AM provides a balanced alternative for near-real-time applications. …”
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A Hybrid ARO Algorithm and Key Point Retention Strategy Trajectory Optimization for UAV Path Planning by Bei Liu, Yuefeng Cai, Duantengchuan Li, Ke Lin, Guanghui Xu

“…However, existing path planning algorithms often encounter problems such as high computational costs and a tendency to become trapped in local optima in complex 3D environments with multiple constraints. …”
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Integration of Solar Energy into Smart Grids: A Cost-Effective Framework for Sustainable Power Management by Ali Raza Larik, Rahool Rai, Kashif Ahmed, Halar Mustafa

“…This system reduces consumer unit costs, ensures a steady electricity supply, enhances the current grid by feeding back excess power, and employs a smart algorithm to select the optimal power source from among the various options. …”
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Robust multi-objective optimization for water flooding under geological uncertainty by Abobakr Sori, Mohammad Sharifi, Nooshin Jabari

“…By employing a multi-objective optimization (MOO) algorithm, we aim to minimize the sensitivity of objective functions to geological variability. …”
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A Shortest Distance Priority UAV Path Planning Algorithm for Precision Agriculture by Guoqing Zhang, Jiandong Liu, Wei Luo, Yongxiang Zhao, Ruiyin Tang, Keyu Mei, Penggang Wang

“…To address these challenges, this study proposes an enhanced Q-learning algorithm designed to optimize UAV path planning by combining static and dynamic obstacle avoidance features. …”
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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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Resilient VPP cost optimization in DER-driven microgrids for large distribution systems considering uncertainty during extreme events by T.D. Suresh, M. Thirumalai, R. Hemalatha, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…Utilizing a modified IEEE 118-bus radial distribution system (RDS), segmented into residential, commercial, and industrial zones, the black widow optimization (BWO) algorithm is employed to optimally size and site VPPs, minimizing operational costs and maximizing system resilience. …”
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Optimized Allocation of Flood Control Emergency Materials Based on Loss Quantification by Wei Wang, Yunqing Wang, Li Huang, Yue Song

“…Compared with the initial allocation, the optimized scheme reduces out‐of‐stock losses by approximately $392,000, lowers transportation costs by over $110,000, and improves the efficiency of flood control emergency scheduling, which can help management make better decisions on the allocation of flood control emergency materials in the future.…”
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Application of Artificial Intelligence with Ant Colony Algorithm in construction projects schedule by Kiana Ahghari

“…So useMethodology of Scheduling of Projects with Artificial Intelligence and with the Approach of Ant Colony Algorithm for Organizations MethodOptimal and practical among other methods. …”
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LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects by Xiaolin WU, Ling LUAN, Lianwu PAN, Hailong LI

“…Compared with the BP neural network and GD-CNN, the proposed model with higher prediction accuracy and stability combines the advantages of Levenberg-Marquart algorithm and convolutional neural network model to improve the calculation effect of power transmission and transformation project cost.…”
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Complementary Filter Optimal Tuning Methodology for Low-Cost Attitude and Heading Reference Systems with Statistical Analysis of Output Signal by Grzegorz Kopecki, Zbigniew A. Łagodowski

“…A simple method for acquiring calibration data is introduced, and these data are subsequently used in the proposed iterative algorithm for optimal time constant selection. The described method minimizes measurement errors and improves the accuracy of the system, ensuring operational stability. …”
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Three-Dimensional Path Planning for Unmanned Aerial Vehicles Based on Hybrid Multi-Strategy Dung Beetle Optimization Algorithm by Hongmei Fei, Ruru Liu, Leilei Dong, Zhaohui Du, Xuening Liu, Tao Luo, Jie Zhou

“…This paper proposes a novel UAV path planning method based on the Hybrid Multi-Strategy Dung Beetle Optimization Algorithm (HMSDBO), which effectively reduces path length and improves path smoothness. …”
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines by Lelisa Wogi, Amruth Thelkar, Tesfabirhan Shoga Tahiro, Tadele Ayana, Shabana Urooj, Samia Larguech

“…This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
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Improved artificial protozoa optimizer: A new method for solar photovoltaic parameter estimation by Wenhao Lai, Duoduo Liu, Jialong Yang, Lei Guo, Weijin Qian, Jiaojiao Wu, Haifeng Zhou

“…We propose an improved Artificial Protozoa Optimizer (iAPO) algorithm for the parameter estimation of photovoltaic cells. …”
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Optimization of Graphene Oxide’s Characteristics with TOPSIS Using an Automated Decision-Making Process by Javanbakht T.

“…Moreover, their advantages and inconveniences could be investigated better once this investigation provides information on optimizing its candidates. In the current research work, a novel automated decision-making process was used with the TOPSIS algorithm using the Łukasiewicz disjunction, which helped detect the confusion of properties and determine its impact on the rank of candidates. …”
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Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm by S. Bharath, A. Vasuki

“…Unlike traditional methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and standard Crow Search Algorithm (CSA), which suffer from premature convergence and limited adaptability to real-time variations, Reinforcement Learning Enhanced Crow Search Algorithm (RL-CSA) which is proposed in this research work solves network reconfiguration optimization problem and minimize energy losses. …”
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Multi-objective particle swarm optimization algorithm-based method for optimal placement and sizing of distributed generations and shunt capacitors in a radial distribution network by Pinank Patel, Nagaraj Patil, Ahmed Mohsen, Aditya Kashyap, Nofal Adrees Hasan, Karthikeyan A, Dhirendra Nath Thatoi, Deepak Gupta, Alireza kamranfar

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Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

“…In this study, a new improved meta-heuristic algorithm is proposed for solving the energy building optimization (EBO) and also hybrid energy systems optimization considering uncertainty of conditioned surface area subjected to temperature control for BEO and renewable power and load uncertainties for hybrid system. …”
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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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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.…”
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