UAV Path Optimization for WSN in Smart Agriculture by Katia Karam, Ali Mansour, Mohamad Khaldi, Benoit Clement, Mohammad Ammad-Uddin

“…The algorithm ensures that the UAV hovers at an optimal position within each sensor’s coverage area, minimizing unnecessary movements. …”
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Application of a novel metaheuristic algorithm inspired by Adam gradient descent in distributed permutation flow shop scheduling problem and continuous engineering problems by Yiqiang Xia, Yanzhe Ji

“…Although these algorithms draw on biological behaviors, their similar heuristic paradigms and modular designs lead to unbalanced exploration and exploitation in complex optimization problems. …”
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A new smart charging electric vehicle and optimal DG placement in active distribution networks with optimal operation of batteries by Bilal Naji Alhasnawi, Marek Zanker, Vladimír Bureš

“…Thirdly, this paper proposes an optimization technique based on the Mountain Gazelle Optimizer (MGO), Improved Beluga Whale Optimization (IBWO), and Arithmetic Optimization Algorithm (AOA) for determining the optimal DGs in radial distribution systems. …”
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Symbiotic Learning Grey Wolf Optimizer for Engineering and Power Flow Optimization Problems by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…This article presents a symbiotic learning-based Grey Wolf Optimizer (SL-GWO) formulated through the introduction of symbiotic hunting and learning strategies to achieve a better trade-off between exploration and exploitation while standing immune to the curse of dimensionality. …”
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Differential evolution-optimized gold nanorods for enhanced photothermal conversion by Aimad Koulali, Piotr Radomski, Paweł Ziółkowski, Francesca Petronella, Luciano De Sio, Dariusz Mikielewicz

“…Utilizing the Differential Evolution (DE) algorithm, a robust metaheuristic optimization approach, we calculated the optimal size and shape of AuNRs for selected wavelengths. …”
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Sensitivity analysis of activity scheduling parameters with a parameter optimization framework by Matheus Moro Zamprogno, Domokos Esztergár-Kiss

“…In this research, the activity chain optimization algorithm is applied, which requires high computational efforts. …”
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Usage of the optimal fuzzy system models on chloride diffusion of concrete by Shuai Sun

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Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization by Haiying Yang, Feiyang Ren, Jingbo Yin, Siqi Wang, Rafi Ullah Khan

“…The Gale–Shapley algorithm is employed to achieve stable vessel–cargo matching, and the genetic algorithm is adopted for iterative optimization. …”
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The Bregman Modified Second APG Method for DC Optimization Problems by Lumiao Wang, Ziye Liu, Chunguang Liu

“…To address this limitation, researchers often employ Bregman distance as an alternative to Euclidean distance in existing DC algorithms. While this substitution relaxes the requirements on DC functions, it simultaneously introduces greater complexity in theoretical analysis. …”
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Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorith... by Mojgan Bordbar, Khabat Khosravi, Changhyun Jun, Dongkyun Kim, Sayed M Bateni, Mahmood Safarzadeh, Hamid Kardan Moghaddam, Shohreh Azizi

“…The LSTM model was optimized using the particle swarm optimizer (PSO) and equilibrium optimizer (EO) metaheuristic algorithms. …”
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An Optimization Method for Multi-Robot Automatic Welding Control Based on Particle Swarm Genetic Algorithm by Lu Chen, Jie Tan, Tianci Wu, Zengxin Tan, Guobo Yuan, Yuhao Yang, Chiang Liu, Haoyu Zhou, Weisi Xie, Yue Xiu, Gun Li

“…This paper introduces an optimization method for multi-robot automated control welding based on a Particle Swarm Genetic Algorithm (PSGA), aiming to address issues such as high costs, large footprint, and excessive production cycles in multi-robot welding production lines. …”
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Learning path planning methods based on learning path variability and ant colony optimization by Jing Zhao, Haitao Mao, Panpan Mao, Junyong Hao

“…Subsequently, an ant colony optimization algorithm is used to generate learning paths. …”
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A Mixed-Integer Convex Optimization Framework for Cost-Effective Conductor Selection in Radial Distribution Networks While Considering Load and Renewable Variations by Oscar Danilo Montoya, Oscar David Florez-Cediel, Luis Fernando Grisales-Noreña, Walter Gil-González, Diego Armando Giral-Ramírez

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Investigation, Optimization of Energy Consumption and Yield Modeling of Two Paddy Cultivars with Genetic-Artificial Bee Colony Algorithm by S. Sharifi, N. Hafezi, M. H. Aghkhani

“…The results of the bee-genetic algorithm optimization revealed that the majority of the consumed resources could be effectively managed on the farm to closely match optimal conditions. …”
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Puma algorithm for environmental emissions and generation costs minimization dispatch in power systems by Badr Al Faiya, Ghareeb Moustafa, Hashim Alnami, Ahmed R. Ginidi, Abdullah M. Shaheen

“…It efficiently navigates the solution space by balancing exploration and exploitation, leveraging puma-like intelligence to minimize both fuel costs and greenhouse gas emissions, including CO2, NOx, and SO2. The POO algorithm is tested on the IEEE 30-bus power system with six thermal units, delivering superior performance compared to advanced optimization algorithms such as the Osprey Optimization Algorithm (OOA), Aquila Optimizer (AO), Slim Mould Algorithm (SMA), Artificial Rabbit Optimization (ARO), and Coati optimization technique. …”
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Enhancing Injector Performance Through CFD Optimization: Focus on Cavitation Reduction by Jose Villagomez-Moreno, Aurelio Dominguez-Gonzalez, Carlos Gustavo Manriquez-Padilla, Juan Jose Saucedo-Dorantes, Angel Perez-Cruz

“…The integration of optimization algorithms further enhances these processes by facilitating studies on mechanical behavior and accelerating iterative operations. …”
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Bio-Inspired Multiobjective Optimization for Designing Content Distribution Networks by Gerardo Goñi, Sergio Nesmachnow, Diego Rossit, Pedro Moreno-Bernal, Andrei Tchernykh

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A computation offloading scheme for energy consumption optimization in Internet of vehicles by Wenxuan GAO, Xinjie YANG

“…In Internet of vehicles (IoV), vehicle-oriented applications are generally computation-intensive and latency-sensitive.Introducing idle computing resources from mobile vehicles as a supplement to network computing power can effectively alleviate the load pressure on edge servers.The problem of task allocation for edge computation offloading in the context of IoV environment were researched.By fully leveraging the combined computing resources of roadside units (RSU), user vehicles, and mobile vehicles within the RSU service range, a computation offloading strategy based on the sparrow search algorithm was proposed and referred to as sparrow search based computation offloading scheme (S²COS), aiming to optimize the overall system energy consumption.In addition, this strategy fully taked into account practical network issues such as service time constraints caused by vehicle mobility and the potential occurrence of computation node failures.The simulation results demonstrate that S²COS can meet the latency requirements for computation-intensive and latency-sensitive tasks, while significantly reducing system energy consumption.…”
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Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm by Faris Kateb, Mahmoud Ragab, Felwa Abukhodair, Omar Ahmed Abdulkader, Louai A. Maghrabi, Sami Saeed Binyamin, Mohammed Khaled Al-Hanawi

“…The bacterial foraging optimization algorithm (BFOA) method is used for feature extraction. …”
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Autonomous Decision-Making for Air Gaming Based on Position Weight-Based Particle Swarm Optimization Algorithm by Anqi Xu, Hui Li, Yun Hong, Guoji Liu

“…To verify the effectiveness of the optimization, a 6v6 aircraft gaming simulation example is provided for comparison, and the experimental results show that the convergence speed of the optimized PW-PSO algorithm is 56.34% higher than that of the traditional PSO; therefore, the algorithm can improve the speed of decision-making while meeting the performance requirements.…”
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