Enhanced Black-Winged Kite Algorithm for Drone Coverage in Complex Fruit Farms by Jian Li, Shengliang Fu, Weijian Zhang, Haitao Fu, Xu Fang, Zheng Li

“…To optimize this problem, we introduce a DWBKA that incorporates a Dynamic Position Balancing strategy and a modified Whale Random Walk strategy, thereby enhancing its global search capability and avoiding local optima traps. …”
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A Novel Genetic Algorithm for Constrained Multimodal Multi-Objective Optimization Problems by Da Feng, Jianchang Liu

“…Extensive experimental verification demonstrates that MTGA-CMMO outperforms other comparative algorithms across multiple test instances and one practical application problem.…”
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Hybrid Swarm Intelligence and Human-Inspired Optimization for Urban Drone Path Planning by Yidao Ji, Qiqi Liu, Cheng Zhou, Zhiji Han, Wei Wu

“…Drawing inspiration from the collective intelligence of animal groups and electoral processes in human societies, this study integrates hierarchical structures and group interaction behaviors into the standard Particle Swarm Optimization algorithm. Specifically, competitive and supportive behaviors are mathematically modeled to enhance particle learning strategies and improve global search capabilities in the mid-optimization phase. …”
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Determined the Edges Using the ant Colony Algorithm and Apply them to Medical Images by Maha Rahman Hasso, Aseel Ali

“…A comparative study is also given illustrating the superiority of the proposed algorithm.…”
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Circle Detection with Adaptive Parameterization: A Bottom-Up Approach by Lin Han, Yan Zhuang, Ke Chen, Yuhua Xie, Guoliang Liao, Guangfu Yin, Jiangli Lin

“…The algorithm implements a local stochastic sampling strategy integrated with a bottom-up circular search mechanism, with all critical parameters in the algorithm derived adaptively based on λ and K, eliminating the need for repetitive hyperparameter search processes. …”
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Application of Improved Whale Algorithm to Optimize Dephosphorization Process Parameters in Converter Steelmaking by Congrui Wu, Yueping Kong

“…The methodology constructs a physics-informed objective function linking process parameters to optimization targets, thereby resolving the disconnect between mechanistic and data-driven modeling approaches. The algorithm innovatively combines Sobol quasi-random sequences with grey wolf social hierarchy strategies to prevent premature convergence in high-dimensional search spaces while maintaining Pareto front diversity, supplemented by a reward mechanism to ensure strict adherence to multi-objective constraints. …”
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Queueing modeling and optimization of hybrid electric vehicle infrastructures using evolutionary algorithms by Shreekant Varshney, Manthan Shah, Bhasuru Abhinaya Srinivas, Mayank Gupta, Kaibalya Prasad Panda

“…The novelty of the proposed research is to formulate the cost optimization problem and demonstrate optimal converging outcomes through an in-depth comparative investigation of multiple evolutionary algorithms, including the particle swarm optimization (PSO), cuckoo search (CS), grey wolf (GW), and honey badger (HB) optimizers. …”
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Content-Aware Fast Motion Estimation Algorithm for IoT Based Multimedia Service by Ryong-Baek, Kyung-Soon Jang, Jae-Hyun Nam, Byung-Gyu Kim

“…In addition, the proposed algorithm achieves a speed-up factor of up to 42.61%, on average, with negligible bitrate degradation, compared with the TZ search motion estimation algorithm for the multiview video coding (TZS) method on HM 10.0.…”
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Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană, Virginia Maria Rădulescu

“…This review presents a structured and data-driven synthesis of 185 peer-reviewed articles, sourced from journals indexed in MDPI and Elsevier, as well as through the Google Scholar search engine, published between 2019 and 2025. The study systematically classifies these articles by plant type, sensor technology, algorithm category, and diagnostic pipeline (detection, localization, resolution). …”
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On the Effectiveness of Nature-Inspired Metaheuristic Algorithms for Performing Phase Equilibrium Thermodynamic Calculations by Seif-Eddeen K. Fateen, Adrian Bonilla-Petriciolet

“…The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. …”
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A new index‐based hyper‐heuristic algorithm for global optimisation problems by Mohammad Reza Hasanzadeh, Farshid Keynia, Maliheh Hashemipour

“…Abstract In this research study, a new combination search algorithm, based on indexing its constituent processes, is proposed to solve global optimisation problems. …”
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Parameter Identification of a Soil Constitutive Model Based on a Hybrid Genetic Differential Evolution Algorithm by Lin Long, Yunyu Li, Peiling Yang, Bo Tang

“…Aiming to address the problem of selecting the parameters of a soil constitutive model in the calculation of foundation pit stability, this paper proposes a hybrid genetic differential evolution algorithm (GADE) which performs by “jumping out of local optima” with “fast convergence” based on the hybrid optimization algorithm strategy and compares the advantages and disadvantages of genetic algorithms (GAs) and differential evolution algorithms (DEs). …”
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An efficient swarm evolution algorithm with probability learning for the black and white coloring problem by Zhiqiang Zhang, Li Zhang, Xiujun Zhang

“…Furthermore, crossover operation, perturbation operation, and tabu search strategy improve the search ability of the algorithm, while evolutionary operation with probability learning mechanism increases the probability of the algorithm finding better solutions. …”
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Improved Exponential and Cost-Weighted Hybrid Algorithm for Mobile Robot Path Planning by Ming Hu, Shuhai Jiang, Kangqian Zhou, Xunan Cao, Cun Li

“…Experimental results demonstrate that, compared to the A* and DWA algorithms, the improved hybrid algorithm enhances search efficiency by 10.93%, reduces search node count by 32.26%, decreases the number of turning points by 36.36% and the value of turning angle by 34.83%, shortens the total path length by 22.05%, and improves overall path smoothness. …”
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Application of genetic algorithm to solving the optimization problem of locations graph vertices in the line by Liubomir Chiriac, Natalia Lupashco, Maria Pavel

“…Instead the genetic algorithm allows selecting good decisions, in a reasonable time, compared to other well-known deterministic or heuristic search engine optimization algorithms. …”
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Obstacle Avoidance Motion Planning of Manipulators in ROS Based on the Improved RRT Algorithm by Cao Yi, Zhang Jingtao, Zhao Pu, Li Lei, Guo Yinhui

“…Aiming at the fact that the RRT algorithm based on the target bias is easy to fall into local search and has a low search efficiency in complex environment, further improvement is made in the ROS based on the Dobot model and the DIY model. …”
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A note on the exclusion operator in multi-swarm PSO algorithms for dynamic environments by Javidan Kazemi Kordestani, Mohammad Reza Meybodi, Amir Masoud Rahmani

“…The exclusion operator is a key component in separating the search territory of each population in multi-population optimisation algorithms for unconstraint continues dynamic optimisation problems (DOPs) with the aim of maintaining the overall diversity of the population and avoiding redundant search. …”
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A genetic algorithm based method of optimizing dispersion matrix for RDSM system by Peng ZHANG, Xiaoping JIN, Dongxiao CHEN

“…Rectangular differential spatial modulation (RDSM) is a multi-antenna incoherent modulation technology with high spectral efficiency, low power consumption, and zero-overhead for channel estimation.RDSM is especially suitable for 6G communication systems, such as fast-moving Internet of vehicles, Internet of things, cellular networks, etc.However, the construction of the sparse rectangular unitary space-time dispersion matrix (DM) at transmitter is a problem.The proposed Genetic algorithm (GA) will result in less computational complexity than the currently used random research.The fitness of GA was calculated by the rank and determinant criterion (RDC) method to avoid discussions in differential system.Due to characteristics of constellation symbols of RDSM, the proposed method reduced the computational complexity during each single iteration in GA.The simulation results show that the optimized DMS can significantly improve the bit error rate (BER) performance of the RDSM system.Compared with random search, the low-complexity GA effectively improves the DMS optimization efficiency of RDSM.The computational complexity required for optimizing DMS is about 0.1% of random search optimization method.…”
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Improved Trimming Ant Colony Optimization Algorithm for Mobile Robot Path Planning by Junxia Ma, Qilin Liu, Zixu Yang, Bo Wang

“…Traditional ant colony algorithms for mobile robot path planning often suffer from slow convergence, susceptibility to local optima, and low search efficiency, limiting their applicability in dynamic and complex environments. …”
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Research on improved RRT path planning algorithm based on multi-strategy fusion by Shangjing Lei, Tengyan Li, Xiaochan Gao, Pengjun Xue, Guozhu Song

“…The simulation results show that in path planning with different map complexity, the simulation results show that the MSF-RRT algorithm reduces the search time, path length, and number of nodes by an average of 90.53%, 16.84%, and 88.43%, respectively, compared to the traditional RRT algorithm; by an average of 79.33%, 14.58%, and 77.71%, respectively, compared to the RRT-Star algorithm; and by an average of 49.74%, 14.89%, and 68.74%, respectively, compared to the RRT- Connect algorithm. …”
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