The Optimal Cost Design of Reinforced Concrete Beams Using an Artificial Neural Network—The Effectiveness of Cost-Optimized Training Data by Jaemin So, Seungjae Lee, Jonghyeok Seong, Donwoo Lee

“…This study presents a method for the automated design of reinforced concrete (RC) beam cross-sections using an artificial neural network (ANN) trained with cost-optimized data generated by the crow search algorithm (CSA). …”
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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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Multicluster Distributed Optimization Strategy for Turbine Wake Environment by Zhenping Yu, Xinmeng Zhou, Yedong Huang, Kunyu Zhou, Guangming Cui, Juntian Qu

“…The experimental results demonstrate that the proposed algorithm can effectively improve the computational efficiency of wake optimization, while ensuring the effect of the wake optimization algorithm in actual wind farms as much as possible, which is more in line with the wake optimization needs of actual wind farms. …”
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Many-Objective Cheetah Optimizer: A Novel Paradigm for Solving Complex Engineering Problems by Pinank Patel, Divya Adalja, Nikunj Mashru, Pradeep Jangir, Arpita, Reena Jangid, G. Gulothungan, Ahmad O. Hourani, Kaznah Alshammari

“…MaOCO represents the Many-Objective Cheetah Optimization Algorithm which draws its concepts from the hunting behavior of cheetahs. …”
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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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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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Solving MRTA problem based on multi-strategy genetic algorithm by CHEN Haiyang, LIU Yan, DOU Wei, HUANG Qi

“…Secondly, the population was divided into three parts to enhance the quality of chromosomes while maintaining randomness. Then, heuristic crossover operators were used to expand the search range of the solution and increase the algorithm′s ability to jump out of local optima. …”
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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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Solving Spatial Optimization Problems via Lagrangian Relaxation and Automatic Gradient Computation by Zhen Lei, Ting L. Lei

“…By automating the (sub)gradient computation, we significantly lower the cost of developing a Lagrangian algorithm for the <i>p</i>-median. And such automation can be applied to numerous other optimization problems.…”
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Usage of the optimal fuzzy system models on chloride diffusion of concrete by Shuai Sun

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Optimizing energy efficiency and indoor thermal comfort in rural self-built housing: A comparative study of GA and EA algorithms by Chen Chen, Yuanyuan Wei

“…This study investigates how building design parameters influence electricity consumption, CO2 emissions, and indoor thermal comfort, and compares the performance of Genetic Algorithm (GA) and Evolutionary Algorithm (EA) in optimizing these objectives. …”
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Encryption Algorithm MLOL: Security and Efficiency Enhancement Based on the LOL Framework by Xinyue Zhang, Daoguang Mu, Wenzheng Zhang, Xinfeng Dong

“…In this paper, we present MLOL, a novel AEAD algorithm based on the LOL framework. MLOL combines authenticated encryption with optimizations to the LFSR structure to enhance both security and efficiency. …”
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Using Optimization Algorithms for Effective Missing-Data Imputation: A Case Study of Tabular Data Derived from Video Surveillance by Mahmoud M. Eid, Kamal ElDahshan, Abdelatif H. Abouali, Alaa Tharwat

“…The first set uses synthetic datasets to compare four optimization algorithms—Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and the Sine–Cosine Algorithm (SCA)—to determine which one best identifies features related to the target feature. …”
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A novel metaheuristic optimizer GPSed via artificial intelligence for reliable economic dispatch by Mahmoud Ibrahim Mohamed, Ali M. Yousef, Ahmed A. Hafez

“…Abstract Recently, meta-heuristic optimization algorithms have enhanced resource efficiency, facilitated informed decision-making, and addressed complex problems involving multiple variables and constraints in engineering and science fields. …”
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Interval valued inventory model with different payment strategies for green products under interval valued Grey Wolf optimizer Algorithm fitness function by Subhash Chandra Das, Md. Al-Amin Khan, Ali Akbar Shaikh, Adel Fahad Alrasheedi

“…To solve the optimization problem, a popular metaheuristic algorithm (viz., Grey Wolf Optimizer) is used and finally performed a post optimality analysis for making a fruitful conclusion.…”
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Efficient feature selection for histopathological image classification with improved multi-objective WOA by Ravi Sharma, Kapil Sharma, Manju Bala

“…To mine optimal feature sets, the suggested technique makes use of a unique variation known as the enhanced multi-objective whale optimisation algorithm. …”
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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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A multistrategy improved hunger games search algorithm by Qiu Yihui, Zhang Xinqiang, Li Ruoyu, Li Dongyi, Xia Feihan

“…The proposed MHGS algorithm provides a novel and effective framework for solving complex optimization problems, demonstrating significant theoretical and practical value in the field of computational intelligence.…”
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Optimal D-STATCOM placement and sizing using a novel bird swarm operated exploitation of elephant herd algorithm by V. Tejaswini, D. Susitra

“…In the 33-bus system at hour 14, the BSOEEH model achieved optimal results, surpassing established methods by significant margins: 1.06% superior to Grey Wolf Optimizer (GWO), 1.02% superior to Whale Optimization Algorithm (WOA), 1.02% superior to the GWO-WOA hybrid model, 0.13% superior to Elephant Herding Optimization (EHO), and 0.93% superior to Backtracking Search Algorithm (BSA). …”
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Quantum Selection for Genetic Algorithms Applied to Electromagnetic Design Problems by Gabriel F. Martinez, Alessandro Niccolai, Eleonora L. Zich, Riccardo E. Zich

“…The method described in this work proposes a hybrid quantum–classical evolutionary optimization algorithm targeting high-frequency electromagnetic problems. …”
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