APPLYING GRAPH THEORY TO OPTIMIZE PRODUCT DELIVERY ROUTES AND MINIMIZE COSTS IN THE RESTAURANT BUSINESS by Наталія Волосова, Наталія Стеблюк, Наталія Небаба, Олена Юдіна, Максим Корнєєв, Ганна Богородицька

“…Routing algorithms based on graphical description are considered the most optimal analysis method for developing optimal product delivery routes, which helps minimize enterprise costs. …”
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An Optimized Method for Solving the Green Permutation Flow Shop Scheduling Problem Using a Combination of Deep Reinforcement Learning and Improved Genetic Algorithm by Yongxin Lu, Yiping Yuan, Jiarula Yasenjiang, Adilanmu Sitahong, Yongsheng Chao, Yunxuan Wang

“…It introduces a novel hybrid approach that combines end-to-end deep reinforcement learning with an improved genetic algorithm. Firstly, the PFSP is modeled using an end-to-end deep reinforcement learning (DRL) approach, named PFSP_NET, which is designed based on the characteristics of the PFSP, with the actor–critic algorithm employed to train the model. …”
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Optimizing high-speed train tracking intervals with an improved multi-objective grey wolf by Lin Yue, Meng Wang, Peng Wang, Jinchao Mu

“…To achieve multi-objective dynamic optimization, a novel train tracking operation calculation method is proposed, utilizing the improved grey wolf optimization algorithm (MOGWO). …”
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Performance Analysis of Battery State Prediction Based on Improved Transformer and Time Delay Second Estimation Algorithm by Bo Gao, Xiangjun Li, Fang Guo, Xiping Wang

“…The Time Delay Second Estimation (TDSE) algorithm optimized the improved Transformer model to overcome traditional models’ limitations in extracting long-term dependency. …”
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Research on Reservoir History Matching Method Based on Real⁃Coded Genetic Algorithm and Connectivity Model by Ainiwaer AILIYAER, Chunli ZHAO, Feng LIU

“…A adaptive selection strategies, crossover, and mutation operations are introduced in this paper to further enhance the algorithm's performance. Application of RGA to the history matching problem in a mechanistic model demonstrates that RGA can effectively improve fitting results and find relatively optimal solutions in a short time. …”
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An artificial neural network and Levenberg-Marquardt training algorithm-based mathematical model for performance prediction by Farheen Bano, Suhail H. Serbaya, Ali Rizwan, Mohammad Shabaz, Faraz Hasan, Hany S. Khalifa

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Predictive Performance of Anti-Lock Braking System with PID Controller Optimized by Gravitational Search Algorithm for a Quarter Car Model: Simulation Modeling and Control by Mohd Sabirin Rahmat, Fauzi Ahmad, Vimal Rau Aparow, Rizauddin Ramli, Sallehuddin Mohamed Haris, Mohd Anas Mohd Sabri, Mohd Anas Mohd Sabri, Meor Iqram Meor Ahmad, Mohd Muhyidin Mustafa

“…This research addresses these issues by developing an ABS model using a quarter-car framework incorporated with a PID controller optimized by using Gravitational Search Algorithm (GSA). …”
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A Framework for Low-Carbon Container Multimodal Transport Route Optimization Under Hybrid Uncertainty: Model and Case Study by Fenling Feng, Fanjian Zheng, Ze Zhang, Lei Wang

“…Subsequently, a multi-strategy improved whale optimization algorithm (WOA) is developed to solve the formulated model. …”
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Reinforcement Learning for Optimizing Renewable Energy Utilization in Buildings: A Review on Applications and Innovations by Panagiotis Michailidis, Iakovos Michailidis, Elias Kosmatopoulos

“…The current review systematically examines RL-based control strategies applied in BEMS frameworks integrating RES technologies between 2015 and 2025, classifying them by algorithmic approach and evaluating the role of multi-agent and hybrid methods in improving real-time adaptability and occupant comfort. …”
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Estimating Daily Reference Crop Evapotranspiration in Northeast China Using Optimized Empirical Models Based on Heuristic Intelligence Algorithms by Zongyang Li, Zhengxin Zhao, Liwen Xing, Lu Zhao, Ningbo Cui, Huanjie Cai

“…After LSM optimization, the simulation accuracy of all models had been significantly improved by 0.58–12.1%. …”
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A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI. by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md Mehedi Hassan

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. …”
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Ultrahigh-Dimensional Model and Optimization Algorithm for Resource Allocation in Large-Scale Intelligent D2D Communication System by Minxin Liang, Jiandong Liu, Jinrui Tang, Ruoli Tang

“…Simulation results show that the developed VGCC-PSO algorithm performs the best in optimizing the UHDO model with up to 6000 dimensionalities. …”
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Low Capillary Elastic Flow Model Optimization Using the Lattice Boltzmann Method and Non-Dominated Sorting Genetic Algorithm by Yaqi Hou, Wei Zhang, Jiahua Hu, Feiyu Gao, Xuexue Zong

“…This paper establishes an LBM multiphase flow model enhanced by machine learning. The hyperparameters of the machine learning model are optimized using the particle swarm algorithm. …”
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Predictive Modeling of Yoga's Impact on Venous Clinical Severity Scoring Using Gaussian Process Classification and Advanced Optimization Algorithms by Yazdan Ashgevari, Faranak Kazemi

“…The study employs the Adaptive Opposition Slime Mould Algorithm (AOSM) and Mountain Gazelle Optimizer (MGO) to enhance the predictive capabilities of a Gaussian Process Classification (GPC) model. …”
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Synergistic Framework for Fuel Cell Mass Transport Optimization: Coupling Reduced-Order Models with Machine Learning Surrogates by Shixin Li, Qingshan Liu, Yisong Chen

“…The combination of the one-dimensional model, the surrogate model, and the genetic algorithm can effectively improve the optimization efficiency.…”
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Optimization of artificial intelligence in localized big data real-time query processing task scheduling algorithm by Maojin Sun, Luyi Sun

“…A task scheduling algorithm optimization model was designed using support vector machine (SVM) and K-nearest neighbor (KNN) combined with fuzzy comprehensive evaluation. …”
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Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

“…To improve the accuracy of dissolved oxygen prediction,this paper researches and proposes a prediction method that combines seagull optimization algorithm (SOA) with support vector machine (SVM) and BP neural network,prepares four prediction schemes based on the monthly dissolved oxygen monitoring data of the Jinghong Power Station in Xishuangbanna,a national important water supply source in Yunnan Province,from January 2009 to September 2020,optimizes the key parameters of SVM and weight threshold of BP neural network by SOA to construct SOA-SVM and SOA-BP models,predicts the dissolved oxygen of Jinghong Power Station based on the models,and compares the prediction results with those of SVM and BP models.The results show that:The absolute values of the average relative errors of the SOA-SVM and SOA-BP models for the 4 schemes of dissolved oxygen prediction are between 4.07%~4.98% and 3.85%~4.83%,and that of the average absolute errors are 0.309~0.374 mg/L and 0.294~0.371 mg/L,respectively.With better prediction accuracy than SVM and BP models,they have good prediction accuracy and generalization ability.SOA can effectively optimize the key parameters of SVM and weight threshold of BP neural network.SOA-SVM and SOA-BP models are feasible for dissolved oxygen prediction,which can provide references for related prediction research.…”
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Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…This work introduces the Deep Learning Model with Evolutionary Computing Approach (DLECA), a novel method for compressing and optimizing hierarchical deep learning models (HDLM). …”
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The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm by MAN Chun-tao, LIU Bo, CAO Yong-cheng

“…In order to improve the precision of the parameter optimization, the research integrates the Particle Swarm Optimization Algorithm with Support Vector Machine, and matches the experimental data, and then establishes a steadystate model of complex process system, which is based on Particle Swarm Optimization Algorithm and Support Vector Machine On the basis of this model, an improved Particle Swarm Optimization Algorithm introduced to Genetic Algorithm is proposed, in order to overcome the defects of Particle Swarm. …”
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An effectiveness of deep learning with fox optimizer-based feature selection model for securing cyberattack detection in IoT environments by Mimouna Abdullah Alkhonaini

“…Furthermore, the FOFSDL-SCD model utilizes the Fox optimizer algorithm (FOA) method for the feature selection process to select the most significant features from the dataset. …”
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