Discrete Sizing Optimization of Steel Structures Using Modified Fireworks Algorithm by Navid Seraji, Mehdi Babaei

“…A total of six benchmark structures including a 10-bar truss, a 25-bar truss, a 582-bar tower truss, a two-bay three-story frame, a one-bay 10-story frame, and a three-bay 24-story frame are chosen from previous studies for the optimization. In addition, a comparison is presented between the results of MoFWA with FWA and other optimization methods such as modified sine-cosine algorithm (MSCA), newton meta-heuristic algorithm (NMA), improved grey wolf optimizer (GWOM), enhanced whale optimization algorithm (EWOA), switching teams algorithm (STA), MHBMO, artificial bee colony (ABC), school-based optimization (SBO), teaching-learning based optimization (TLBO), design-driven harmony search (DDHS), and inscribed hyperspheres (IHS). …”
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A study on the prediction of mountain slope displacement using a hybrid deep learning model by Yuyang Ma, Xiangxiang Hu, Yuhang Liu, Yaya Shi, Zhiyuan Yu, Xinmin Wang, Liangbai Hu, Shuailing Liu, Dongdong Pang

“…Abstract To address the challenges of large prediction errors and limited reliability in conventional modeling approaches, this study proposes a hybrid framework that integrates optimization and deep learning techniques. The method employs an Improved Whale Optimization Algorithm (IWOA) to fine-tune parameters for GNSS data fitting, ensuring accurate signal feature extraction. …”
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A hybrid particle swarm optimization algorithm for solving engineering problem by Jinwei Qiao, Guangyuan Wang, Zhi Yang, Xiaochuan Luo, Jun Chen, Kan Li, Pengbo Liu

“…Abstract To overcome the disadvantages of premature convergence and easy trapping into local optimum solutions, this paper proposes an improved particle swarm optimization algorithm (named NDWPSO algorithm) based on multiple hybrid strategies. …”
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Optimization the stochastic optimal reactive power dispatch with renewable energy resources using a modified dandelion algorithm. by Naima Agouzoul, Aziz Oukennou, Faissal Elmariami, Mohamed Ebeed, Jamal Boukherouaa, Rabiaa Gadal, Mokhtar Aly, Emad A Mohamed

“…The Comparative results demonstrate that the MDO algorithm is the best for solution the SORPD against sand cat swarm optimization (SCSO), gorilla troop optimizer (GTO), harmony search (HS), and Beluga whale optimization (BWO).…”
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YOLO-WWBi: An Optimized YOLO11 Algorithm for PCB Defect Detection by Yi Zhao, Zhidi Jiang

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Distributed K-Means algorithm based on a Spark optimization sample. by Yongan Feng, Jiapeng Zou, Wanjun Liu, Fu Lv

“…To address the instability and performance issues of the classical K-Means algorithm when dealing with massive datasets, we propose SOSK-Means, an improved K-Means algorithm based on Spark optimization. …”
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Application of Blocplan and Aldep Algorithms for Optimizing Production Layout at Meatball Factory by Thabed Tholib Baladraf

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The WSN Localization Algorithm Integrating Ranging Correction and Spider Wasp Optimization by YU Xiu-wu, XIAO Lin, LIU Yong, YE Lai

“…The objective is to improve the accuracy of node localization and enhance the overall performance of the DV-Hop algorithm, making it more reliable in practical deployment scenarios.MethodsThe proposed algorithm consists of two main components: distance correction and optimization using Spider Wasp Optimization (SWO). …”
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A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations by WANG Kechao, CAI Ruoyi, SHEN Jianjian

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. …”
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A Group Search Algorithm for Optimal Scheduling of Cascade Hydropower Stations by WANG Kechao, CAI Ruoyi, SHEN Jianjian

“…The coronavirus herd immunity optimizer (CHIO) algorithm was introduced to address the optimal scheduling problem of cascade hydropower plants, and an improved algorithm called LCHIO was proposed. …”
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EG-DPoS: Optimized DPoS Consensus Algorithm Based on Evolutionary Game by LIU Yong, DENG Xiaohong, LIU Lihui, SHI Yiran, ZHANG Li

“…The proportional coefficient of credit value and voting weight in the process of agent node election is balanced to reduce the oligopoly phenomenon caused by nodes with high credit value, while the roulette selection algorithm is used to randomize the block generation order of agent nodes, to avoid nodes being attacked during block generation and improve the security of the system. …”
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Hybrid strategy enhanced crayfish optimization algorithm for breast cancer prediction by Yu-Jiong Li

“…When combined with Extreme Learning Machine (ELM) and applied to the Wisconsin breast cancer dataset, the MSCOA-ELM model achieved 100% accuracy and F1 score, a 28.9% improvement over the baseline ELM, demonstrating the algorithm’s efficiency and generalization ability in solving practical optimization problems.…”
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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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Optimal performance design of bat algorithm: An adaptive multi‐stage structure by Helong Yu, Jiuman Song, Chengcheng Chen, Ali Asghar Heidari, Yuntao Ma, Huiling Chen, Yudong Zhang

“…Abstract The bat algorithm (BA) is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness, which can be used to find the globally optimal solutions for various optimisation problems. …”
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Investigation of a Multi-Strategy Ensemble Social Group Optimization Algorithm for the Optimization of Energy Management in Electric Vehicles by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…A multi-strategy ensemble social group optimization algorithm (ME-SGO) to improve the exploration for complex and composite landscapes through distance-based strategy adaption and success-based parameter adaption while incorporating linear population reduction is proposed. …”
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Multi-AGV multitask collaborative scheduling based on an improved ant colony algorithm by Yazhen Zhu, Qing Song, Meng Li

“…This paper establishes a mathematical model with the optimization objective of minimizing the overall running time of material distribution tasks and proposes an improved ant colony algorithm to optimize the model. …”
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Research on Multi-Target Point Path Planning Based on APF and Improved Bidirectional RRT* Fusion Algorithm by Zijian Bian, Gang Li, Xizheng Wang

“…This study also aims to improve the RRT* algorithm by using optimization strategies such as bidirectional sampling and adding an adaptive target bias strategy to improve its efficiency in obtaining global paths. …”
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Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization by Fan Zhang, Chuankai Liu, Peng Liu, Shuiting Ding, Tian Qiu, Jiajun Wang, Huipeng Du

“…Abstract This study proposes BAGWO, a novel hybrid optimization algorithm that integrates the Beetle Antennae Search algorithm (BAS) and the Grey Wolf Optimizer (GWO) to leverage their complementary strengths while enhancing their original strategies. …”
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Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks by S. Yazhinian, S. Famila, P. Jose, Mahendar A, Sofia R

“…It is seen that the proposed RadB_SOA achieves 12.4 % of transmission error, 14.6 % of ranging error, 96.3 % of localization coverage, 98.65 % of PDR, and 21.56 % of energy consumption. • The Radial Bias-Seeker Optimization Algorithm (RadB_SOA) suggested enhances the precision in target localization and optimizes energy usage in wireless sensor networks. • Simulation outcomes reveal improved tracking accuracy, minimized transmission and ranging errors, as well as increased localization coverage over current techniques. • The research presents an extensive evaluation of particle count fluctuations in RBSO, demonstrating enhanced positioning speed and precision with network efficiency.…”
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Research on Algorithms for Local Robot Positioning Using Methods of Discrete Optimization by Vyacheslav Korolyov, Maksim Ogurtsov, Oleksandr Khodzinskyi

“…For constructing the relative coordinate system, a method of forming a base triangle using a nonlinear discrete optimization method was proposed. An algorithm for building a local positioning system for a robot group was developed to ensure the stable configuration of the group in the absence of access to global or cellular navigation systems while performing tasks in two-dimensional spaces. …”
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