A Comparison of Heuristic Algorithms for Solving the Traveling Salesman Problem by Younes Khdeir, Ahmed Awad

“…The study examines how these algorithms can solve the TSP and avoid local minimum values while achieving a balance between research exploration and exploitation for an optimal solution. …”
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Observation optimization for marine target tracking by airborne and maritime unmanned platforms cooperation using adaptive enhanced dung beetle optimization by Qiuyang Dai, Faxing Lu, Haoran Shi, Junfei Xu, Jianjing Qu

“…Existing research predominantly focuses on homogeneous platform cooperative observation optimization under random error influences, while neglecting the collaborative optimization challenges of heterogeneous platforms affected by systematic errors. …”
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Legendre Cooperative PSO Strategies for Trajectory Optimization by Lei Liu, Yongji Wang, Fuqiang Xie, Jiashi Gao

“…Finally, in the numeral simulations, compared with the ordinary PSO and other typical intelligent optimization algorithms GA and DE, the proposed LCPSO has traits of lower dimension, faster speed of convergence, and higher accuracy, while providing smoother control variables.…”
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Optimizing high voltage gain interleaved boost converters for PV and wind systems using hybrid deep learning with bitterling fish and secretary bird algorithms by G.Veera Sankara Reddy, S. Vijayaraj

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Optimal Protection Coordination for Grid-Connected and Islanded Microgrids Assisted by the Crow Search Algorithm: Application of Dual-Setting Overcurrent Relays and Fault Current L... by Hossien Shad, Hamid Amini Khanavandi, Saeed Abrisham Foroushan Asl, Ali Aranizadeh, Behrooz Vahidi, Mirpouya Mirmozaffari

“…The objective is to minimize the combined annual investment and expected operational costs while adhering to the optimal power flow equations governing the MG, which incorporates both DGs and ESSs. …”
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OPTIMIZATION OF FUZZY INVENTORY MANAGEMENT IN INDUSTRIAL PROCESSES USING DEEP LEARNING ALGORITHMS: A HYBRID APPROACH FOR ENHANCING DEMAND FORECASTING AND SUPPLY CHAIN EFFICIENCY by K. Kalaiarasi*, S. Swathi

“…By transforming data into fuzzy sets and applying neural networks for demand forecasting, the proposed model optimizes inventory levels to reduce costs and prevent stockouts. …”
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Isolation Enhancement Based on TM010 and TE30 Mode Characteristics in a Patch Antennas Using Genetic Algorithm Optimization for Ku-Band Applications by Muddineni Raveendra, U. Saravanakumar, P. Padmaloshani, P. Saam Prasanth Dheeraj, Anand Anbalagan, R. Sreelakshmy

“…The design utilized a Rogers 3003 series dielectric substrate with a dielectric constant of 3.3 and a loss tangent of 0.003. A genetic algorithm with tournament selection and a multiobjective function was applied to optimize key performance metrics, such as impedance matching, bandwidth, and gain. …”
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Supply chain management and optimization in transportation logistics by Saoussen Krichen

“…These two classes can scan all problem sizes while generating optima and near optimal solution. …”
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Optimization of additive contents in cottonseed meals during the solid-state fermentation using response surface methodology and artificial neural network-based genetic algorithm by TANG Jiang-wu, SUN Hong, YAO Xiao-hong, WU Yi-fei, WANG Xin

“…The correlation efficiency of 0.9191 identified by response surface methodology was a little lower than that of 0.9991 identified by genetic algorithm based on an artificial neural network model, which also was with a lower RMSE value by 0.13, indicating that the artificial neural network-based genetic algorithm had a much higher optimizing ability and modeling ability during the optimization of the solid-state fermentation process.…”
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GenePixKolor (GPK) Fusion: A Novel Evolutionary Algorithm-Based Optimized NFT Card Generation and Rarity Ranking Method for Gaming Tokenomics by J. Guruprakash, P. Pradeep, L. B. Krithika

“…GPK Fusion leverages genetic algorithms, image processing and machine learning to create a comprehensive, four-stage system that optimizes both the trait generation and visual appeal of NFTs, while providing an advanced rarity ranking mechanism. …”
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Enhanced data-driven shear strength predictive modeling framework for RCDBs using explainable boosting-based ensemble learning algorithms coupled with Bayesian optimization by Imad Shakir Abbood, Noorhazlinda Abd Rahman, B.H. Abu Bakar

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Engine performance and emission optimization with waste cooking oil biodiesel/diesel blend using ANN and RSM techniques coupled with ACKTR-DE and HHO algorithms by Mehmet Ali Biberci, Mustafa Bahattin Çelik, Esma Ozhuner

“…By applying the developed model, the brake thermal efficiency (BTE) response was optimized to its maximum value, while all other responses were minimized. …”
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A hybrid model for short-term offshore wind power prediction combining Kepler optimization algorithm with variational mode decomposition and stochastic configuration networks by Bingbing Yu, Yonggang Wang, Jun Wang, Yuanchu Ma, Wenpeng Li, Weigang Zheng

“…Firstly, the series of wind power data is decomposed using the VMD method optimized by the KOA, aiming to smooth the wind power series while preserving its inherent characteristics. …”
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An Image Fusion Algorithm for Sustainable Development Goals Satellite-1 Night-Time Light Images Based on Optimized Image Stretching and Dual-Domain Fusion by Kedong Li, Bo Cheng, Xiaoming Li, Xiaoping Zhang, Guizhou Wang, Jie Gao, Qinxue He, Yaocan Gan

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Comparative Global Assessment and Optimization of LandTrendr, CCDC, and BFAST Algorithms for Enhanced Urban Land Cover Change Detection Using Landsat Time Series by Taku Murakami, Narumasa Tsutsumida

“…This study aims to systematically evaluate and optimize three widely used algorithms—LandTrendr, CCDC, and BFAST—selected for their proven capabilities in different land cover change contexts and distinct algorithmic approaches. …”
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Power quality enhancement based disturbance rejection controller in microgrid system using walrus optimization algorithm and multi-functional recurrent fuzzy neural network by Ali M.H. Al Thaiban, Akram Elmitwally, Abdelhady Ghanem, Ahmed I. Omar

“…The UPQC’s control is executed through a Fractional Order-Active Disturbance Rejection Controller (FOADRC) that employs the Innovative Walrus Optimization Algorithm (WOA) to ascertain optimal gain values for the control method across numerous PQ scenarios, while the Multi-Functional Recurrent Fuzzy Neural Network (MFRFNN) predicts control parameters for adaptive system regulation. …”
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Dual-platform integration of HPTLC and firefly algorithm-optimized chemometrics with hammersley sequence sampling for simultaneous quantification of bisoprolol, amlodipine, and mut... by Lateefa A. Al-Khateeb, Ahmed Emad F. Abbas, Mohamed R. Elghobashy, Nisreen F. Abo Talib, Ibrahim A. Naguib, Mohammed Alqarni, Michael K. Halim

“…This work establishes a new paradigm in sustainable pharmaceutical analysis, demonstrating how algorithmic optimization and environmental consciousness can synergistically advance analytical science while meeting stringent regulatory requirements.…”
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Optimization of anti-MRSA compound production by Streptomyces sp. AR05 using an integrated RSM-ANN-GA approach by Fateh Merouane, Amani Kifadji, Racha Mansouri, Meroua Safa Mechouche, Chemes El-Houda Messaad, Anfal Bellebcir

“…Using the PlackettBurman design, the most important variables affecting the anti-MRSA activity were found to be peptone, CaCO3, and pH. These factors were optimized using Box-Behnken design, while RSM and ANN were utilized for modeling the experimental data. …”
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Multiobjective Time-Space Grid Optimization of Lithium-Ion Electrochemical Model Based on Stability Analysis and Limit Region Decoupling Strategy by Libin Zhang, Minghang Zhang, Hongying Shan, Guan Xu, Jingsheng Dong, Xuemeng Bai

“…A multi-objective time space grid optimization model was developed and solved using a multi-objective artificial bee colony algorithm. …”
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Hybrid Population-Based Hill Climbing Algorithm for Generating Highly Nonlinear S-boxes by Oleksandr Kuznetsov, Nikolay Poluyanenko, Kateryna Kuznetsova, Emanuele Frontoni, Marco Arnesano

“…The HPHC algorithm maintains high reliability across diverse parameter settings while requiring minimal computational resources, making it particularly suitable for practical cryptographic applications.…”
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