Global–Local Cooperative Optimization in Photonic Inverse Design Algorithms by Mingzhe Li, Tong Wang, Yi Zhang, Yulin Shen, Jie Yang, Ke Zhang, Dehui Pan, Ming Xin

“…Compared to the conventional Direct Binary Search (DBS), the GLINT algorithm not only significantly enhances computational efficiency through its global search–local refinement framework but also achieves a superior 20 nm × 20 nm optimization resolution while maintaining its optimization speed—substantially advancing the design capability. …”
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Mathematical Models and Algorithms of Optimal Load Management of Electricity Consumers by I. U. Rakhmonov, K. M. Reymov

“…Based on the calculated-and-experimental studies, it was determined that the proposed mathematical model of the problem is adequate, while the developed algorithms for optimal planning of short-term power system modes with optimization of load profile of regulated electricity consumers and taking into account various types of limitations are of high computational qualities.…”
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Detection of Plants Leaf Diseases using Swarm Optimization Algorithms by Saud Abdul Razzaq, Baydaa Khaleel

“…In the second stage, the features were extracted based on the statistical feature extraction method, while in the third stage, the particle swarm (PSO) and chicken swarm optimization(CSO) algorithms were used to diagnose and classify plant diseases. …”
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Modified Whale Optimization Algorithm for Multiclass Skin Cancer Classification by Abdul Majid, Masad A. Alrasheedi, Abdulmajeed Atiah Alharbi, Jeza Allohibi, Seung-Won Lee

“…Our method outperforms the genetic algorithm (GA), Particle Swarm Optimization (PSO), and the slime mould algorithm (SMA), as well as deep learning-based skin cancer classification models, which have reported accuracies of 87% to 94% in previous studies. …”
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Studying the Possibility of Optimizing the Statin Therapy Algorithm in Outpatient Practice by D. V. Nebieridze, N. M. Akhmedzhanov, S. A. Davitashvili, A. S. Lishuta, A. S. Safaryan

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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…Optimizing soil nutrient prediction models is important for achieving maximum agricultural output and sustainability while also ensuring effective resource management and environmental protection, as demonstrated by a case study in Johannesburg, South Africa. …”
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Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

“…The focus is on maximizing the monitored area while minimizing energy usage. A Scalable coverage-based particle swarm optimization (SCPSO) algorithm integrates a probabilistic coverage model based on Euclidean distance to detect coverage gaps and guide the optimal positioning of nodes, ensuring that each target within the region of interest is covered by at least one sensor. …”
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Stock portfolio optimization using hill climbing and simple human learning optimization algorithms as a decision support system by Suyash S. Satpute, Amol C. Adamuthe, Pooja Bagane

“…The goal of this research is to develop a decision support system for stock portfolio optimization using hill climbing and SHLO algorithms based on fundamental analysis of stocks. …”
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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

“…However, traditional optimization algorithms struggle with local convergence and accuracy in large-scale sensor deployment, an NP-hard problem. …”
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Research on Collaborative Optimization Strategy of Railway Signal Nonlinear Control System Based on BBO Algorithm and Multi-objective Optimization by Xue Li, Yixuan Yang, Zheng Li, Hui He

“…This study focuses on exploring collaborative optimization strategies for a nonlinear control system of railway signals based on the BBO algorithm. …”
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The Three-Stage Strategy of Bi-Level Optimal Energy Management in the Distribution-Home Network Based on Golf Optimization Algorithm by Javad Goodarzi, Mohammad Tolou Askari, Meysam Amirahmadi, Majid Babaeinik

“…The framework is supported by a bi-level optimization model that addresses the optimal management of both electrical and thermal energy within home microgrids, while also integrating electricity and heat distribution networks. …”
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Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems by Thang Trung Nguyen, Thai Dinh Pham, Le Chi Kien, Le Van Dai

“…This paper proposes an improved coyote optimization algorithm (ICOA) for optimizing the location and sizing of solar photovoltaic distribution generation units (PVDGUs) in radial distribution systems. …”
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A Novel Optimization Algorithm Inspired by Egyptian Stray Dogs for Solving Multi-Objective Optimal Power Flow Problems by Mohamed H. ElMessmary, Hatem Y. Diab, Mahmoud Abdelsalam, Mona F. Moussa

“…One of the most important issues that can significantly affect the electric power network’s ability to operate sustainably is the optimal power flow (OPF) problem. It involves reaching the most efficient operating conditions for the electrical networks while maintaining reliability and systems constraints. …”
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Joint Optimization of Computation Offloading and Task Scheduling Using Multi-Objective Arithmetic Optimization Algorithm in Cloud-Fog Computing by Asad Ali, Nazia Azim, Mohamed Tahar Ben Othman, Ateeq Ur Rehman, Masoud Alajmi, Mosleh Hmoud Al-Adhaileh, Faheem Ullah Khan, Mamyrbayev Orken, Habib Hamam

“…Extensive simulations in MATLAB demonstrate the efficacy of the proposed algorithm in terms of designated optimization objectives.…”
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Application of improved particle swarm optimization algorithm combined with genetic algorithm in shear wall design by Wei Gao

“…The example results show that when using the designed shear wall design program for scheme design, the success rate reaches 100 %, which is 38.47 % higher than the original particle swarm optimization algorithm. The obtained optimization scheme has interlayer displacement angles of 1/2096 and 1/1800 in the vertical and horizontal directions, respectively, while the torsional displacement ratio in both directions is 1.0908 and the torsional period ratio is 0.7125. …”
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Multi-Focus Image Fusion Using Energy Valley Optimization Algorithm by Harun Akbulut

“…The obtained experimental results are compared with the well-known Genetic Algorithm (GA), Differential Evolution Algorithm (DE), and Artificial Bee Colony Optimization Algorithm (ABC). …”
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Exploring the Orca Predation Algorithm for Economic Dispatch Optimization in Power Systems by Vivi Aida Fitria, Arif Nur Afandi, Aripriharta

“…This research shows that Orca Predation Algorithm consistently does better than other bio-inspired algorithms like Particle Swarm Optimization, Whale Optimization Algorithm, Grey Wolf Optimizer, the Bat Algorithm, Genetic Algorithm and Ant Colony Optimization in terms of minimum cost, average cost, and solution stability. …”
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A novel robust multi-objective evolutionary optimization algorithm based on surviving rate by Wenxiang Jiang, Kai Gao, Shuwei Zhu, Lihong Xu

“…Despite the success of multi-objective evolutionary optimization algorithms in addressing complex optimization problems, research focusing on input disturbances remains limited. …”
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Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

“…The PLO algorithm generates SSE results of 0.025493 for BCS 500 W and 0.275211 for Nedstack 600 W PS6 and 0.283774 for STD 250 W Stack while keeping AE at 0.259293 and RE% at 1.185075 for the STD 250 W Stack. …”
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Optimizing Trajectories for Rechargeable Agricultural Robots in Greenhouse Climatic Sensing Using Deep Reinforcement Learning with Proximal Policy Optimization Algorithm by Ashraf Sharifi, Sara Migliorini, Davide Quaglia

“…In this paper, we propose a method based on Deep Reinforcement Learning enriched with a Proximal Policy Optimization (PPO) algorithm for determining the best trajectory an agricultural robot must follow to balance the number of measurements and autonomy adequately. …”
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