A pursuit-evasion game robot controller design based on a neural network with an improved optimization algorithm by Mustafa Wassef Hasan, Luay G. Ibrahim

“…The neural network weights are learned using an improved sine cosine algorithm based on chaotic theory (ISCACT). The ISCACT is proposed to solve and avoid the proposed game of being trapped in the local minimum problem. …”
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A heuristic decomposition algorithm to optimally configure superconducting fault current limiters in Large-Scale power systems by Chuqin Wu, Mingbo Liu, Zihan Zhang, Min Xie

“…To accelerate the solution of the MILP problem, a heuristic decomposition algorithm was proposed based on Analytical Target Cascading (ATC) and a Large Neighborhood Search (LNS) algorithm, which has two stages. …”
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UAV Real-Time Target Detection and Tracking Algorithm Based on Improved KCF and YOLOv5s_MSES by Shihai Cao, Ting Wang, Tao Li, Shumin Fei

“…Additionally, on the OTB100 dataset, the proposed algorithm demonstrates significant improvements in distance precision (DP) metrics across four challenging attributes compared to the baseline algorithm, showing a 12.85% increase for scale variation (SV), 16.45% for fast motion (FM), 18.66% for occlusion (OCC), and 17.09% for out-of-view (OV) scenarios. …”
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Gradient-Enhanced Kriging-Based Parallel Efficient Global Optimization Algorithm and Its Application in Aerodynamic Shape Optimization by Hang Fu, Qingyu Wang, Takuji Nakashima, Asahi Kawasaki, Chenguang Lai, Keigo Shimizu, Rahul Bale, Makoto Tsubokura

“…The parallel efficient global optimization (EGO) algorithm was developed to leverage the rapid advancements in high-performance computing. …”
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Modeling and Solving the Knapsack Problem with a Multi-Objective Equilibrium Optimizer Algorithm Based on Weighted Congestion Distance by Ziqian Wang, Xin Huang, Yan Zhang, Danju Lv, Wei Li, Zhicheng Zhu, Jian’e Dong

“…Although our MOEO_WCD algorithm covers less of the composite front in the objective space compared with the MODE algorithm for knapsack problem 1, its coverage of the integrated reference solutions in the decision space is greater than that of the MODE algorithm. …”
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Comparing the Effectiveness of Artificial Intelligence Models in Predicting Ovarian Cancer Survival: A Systematic Review by Farkhondeh Asadi, Milad Rahimi, Nahid Ramezanghorbani, Sohrab Almasi

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Efficient Technique for Joint Parameter Estimation of Mixed Far Field Targets and Near Field Jammers in Phased Array Radar by Fawad Zaman, Sadiq Akbar, Zohaib Akhtar, Gridsada Phanomchoeng

“…The proposed schemes are not only compared with each other but also with the state-of-the-art MUSIC algorithm. …”
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Simplifying Multiproject Scheduling Problem Based on Design Structure Matrix and Its Solution by an Improved aiNet Algorithm by Chunhua Ju, Tinggui Chen

“…Subsequently, aiNet algorithm comprised of clonal selection, negative selection, and network suppression is adopted to realize the local searching and global searching, which will assure that it has a powerful searching ability and also avoids the possible combinatorial explosion. …”
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Enhancing Path Planning for Autonomous Robots in Large, Obstacle-Crowded Environments: A Practical Improvement to the PRM Algorithm by Shimon Aviram, Eugene Levner

“…Additionally, when encountering obstacles, the algorithm searches for detour options in relatively small, obstacle-crowded subareas rather than processing each obstacle individually or the entire map. …”
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An Optimization Model for Shell Plate Seam Landing Using Minimum Manufacturing Cost and a Solution by Genetic Algorithm by Ho Rim Pae, Min Hyok Jon, Chol Jun Pak

“…We consider a shape optimization problem that the optimal solution is searched among the possible alternatives when the position and shape of the seams are changed and apply the genetic algorithm to the solution of this shape optimization problem. …”
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Comparison of Clustering Algorithms: Fuzzy C-Means, K-Means, and DBSCAN for House Classification Based on Specifications and Price by Dhendy Mardiansyah Putra, Ferian Fauzi Abdulloh

“…This study aims to compare the performance of three clustering algorithms, namely Fuzzy C-Means, K-Means, and DBSCAN, in grouping houses based on their specifications and prices. …”
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CO2 Emission-Constrained Short-Term Unit Commitment Problem Using Shuffled Frog Leaping Algorithm by K. Selvakumar, D. Selvabharathi, R. Palanisamy, T. M. Thamizh Thentral

“…This paper proposes an integer-coded shuffled frog-leaping algorithm (SFLA) to minimize both total CO2 emissions and operating costs for the unit commitment problem (UCP) over a one-day scheduling period. …”
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An innovative coverage optimization method for smart information monitoring in agricultural IoT using the multi-strategy Pelican optimization algorithm by Wei Chen, Qike Cao, Bingyu Cao, Bo Jin

“…Comparative experiments with Improved Artificial Bee Colony Algorithm (IABC), Chaotic Adaptive Firefly Optimization Algorithm (CAFA), Adaptive Particle Swarm Optimization (APSO), and Lévy Flight Strategy Chaotic Snake Optimization Algorithm (LCSO) demonstrate that MSPOA improves network coverage by 5.85%, 11.33%, 21.05%, and 20.66%, respectively. …”
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Risk Assessment of Supplier R&D Investment Based on Improved BP Neural Network by Yinghua Song, Xiaoyan Sang, Zhe Wang, Hongqian Xu

“…By leveraging the ability of particle swarm optimization (PSO), whale optimization algorithm (WOA), and genetic algorithm (GA) to search for global optimal solutions, the BP neural network is improved to avoid becoming trapped in local optimal solutions and enhance the model’s generalization ability. …”
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Research on the Optimization Method of Visual Sensor Calibration Combining Convex Lens Imaging with the Bionic Algorithm of Wolf Pack Predation by Qingdong Wu, Jijun Miao, Zhaohui Liu, Jiaxiu Chang

“…The comparative experimental results show that the average reprojection errors of the simulated annealing algorithm, Zhang’s calibration method, the sparrow search algorithm, the particle swarm optimization algorithm, bionic algorithm of Wolf Pack Predation, and the algorithm proposed in this paper (CLI-WPP) are 0.42986500, 0.28847656, 0.23543161, 0.219342495, 0.10637477, and 0.06615037, respectively. …”
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An efficient hybrid algorithm based on particle swarm optimisation and teaching‐learning‐based optimisation for parameter estimation of photovoltaic models by Dianlang Wang, Zhongrui Qiu, Qi Yin, Haifeng Wang, Jing Chen, Chengbi Zeng

“…Typically, each group has its particular movement pattern concentrating on exploration or exploitation respectively to improve the search efficiency of the algorithm. Furthermore, to deal with individuals beyond the boundary, a new designed probabilistic rebound strategy is introduced, which increases the diversity of population and avoids population aggregation at the search boundary. …”
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An enhanced fruit fly optimization algorithm with random spare and double adaptive weight strategies for oil and gas production optimization by Xu Wang, Jingfu Shan

“…These evaluations include ablation studies, scalability analyses, visualization of search trajectories, and comparative assessments against state-of-the-art algorithms. …”
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A practical vehicle routing problem in small and medium cities for fuel consumption minimization by Yong-Jin Pak, Kyong-Ho Mun

“…The proposed algorithm can decrease fuel consumption by 25 % compared to manual routing and scheduling. …”
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Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…Based on the reconstructed data, traditional Support Vector Regression (SVR) models and SVR models optimized by the Grid Search Method (GSM) are constructed. Furthermore, Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Marine Predators Algorithm (MPA), and Whale Optimization Algorithm (WOA) are introduced to optimize the SVR model, and the prediction performance is compared with that of the Long Short-Term Memory (LSTM) model. …”
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A Multi-Strategy ALNS for the VRP with Flexible Time Windows and Delivery Locations by Xiaomei Zhang, Xinchen Dai, Ping Lou, Jianmin Hu

“…To solve this problem, a Multi-Strategy Adaptive Large Neighborhood Search (MSALNS) method is proposed. Operators guided by strategies such as backtracking and correlation are introduced to create different neighborhoods for ALNS, thereby enriching search diversity. …”
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