Proposing a flood management solution based on optimal usage allocation via genetic algorithm by Davood Mokhtari, Aliakbar Rasouli, Monire Moosabeigi

“…Conclusion: The results and achievements of this study include proposing a land use optimization model based on a multi-objective genetic algorithm for flood reduction, integrated river basin management, as well as programming in an expansive form to use in future studies.…”
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Research on Pump Down Treating Pressure Prediction Based on New Particle Swarm Optimization Algorithm by LIU Mingming, SONG Zhiyong, MA Shou, WEI Yuhua, ZHUANG Huanle

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Optimal Design of Linear Quadratic Regulator for Vehicle Suspension System Based on Bacterial Memetic Algorithm by Bala Abdullahi Magaji, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…BMA combines the bacterial foraging optimization algorithm (BFOA) and the memetic algorithm (MA) to enhance the effectiveness of its search process. …”
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Energy optimization and plant comfort management in smart greenhouses using the artificial bee colony algorithm by Muhammad Jawad, Fazli Wahid, Sikandar Ali, Yingliang Ma, Ahmed Alkhyyat, Jawad Khan, Youngmoon Lee

“…The overall efficacy of the fuzzy controllers that switch On/Off the actuators was obtained by minimizing the error between the best estimates of environmental factors and the ABC optimized values. Additionally, the suggested method was contrasted with other effective algorithms, such as Genetic Algorithm (GA), Firefly Algorithm (FA), and Ant Colony Optimization (ACO). …”
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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 centerline symmetry and double-line transformation based algorithm for large-scale multi-objective optimization by Xiangjuan Wu, Yuping Wang, Ziqing Wang

“…It is very challenging to design efficient algorithms for LSMOPs to search the whole space effectively and balance the convergence and diversity at the same time. …”
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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

“…A genetic algorithm with a quantum selection operator that applies high selection pressure while preserving selection diversity is introduced. …”
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A Study on Container Storage Optimization in Yards Based on a Hyper-Heuristic Algorithm with a Q-Learning Mechanism by Lifen Chen, Jiajun Lin, Shihao Xu

“…The objective is to minimize the carbon emissions and the number of container rehandling operations in ports, for which a mixed-integer linear programming model is built. Both heuristic algorithms and hyper-heuristic algorithms are employed to optimize the container storage plan, and their applicability in storage optimization is compared. …”
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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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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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A Comparative Analysis of Advanced Routing and Cluster Head Selection Algorithm Using Lagrange Interpolation by Zoren P. Mabunga, Jennifer C. Dela Cruz, Renato R. Maaliw

“…This paper presents a unified performance metric for evaluating the chronological wild geese optimization (CWGO) algorithm in wireless sensor networks (WSNs). …”
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An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

“…Feature selection is a crucial data processing method used to reduce dataset dimensionality while preserving key information. In this paper, we proposed a multi-strategy enhanced dung beetle optimization algorithm (mDBO) that integrates multiple strategies to effectively address the feature selection problem. …”
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Application of Artificial Intelligence with Ant Colony Algorithm in construction projects schedule by Kiana Ahghari

“…So useMethodology of Scheduling of Projects with Artificial Intelligence and with the Approach of Ant Colony Algorithm for Organizations MethodOptimal and practical among other methods. …”
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Developing an Optimization Model for Minimizing Solid Waste Collection Costs by Muciz Özcan, Semih Cengiz, Mehmet Şen

“…The Simulated Annealing (SA) algorithm, one of the heuristic optimization techniques used to identify the best solutions to complicated problems, is employed to solve the routing problem of solid waste collection vehicles in this study. …”
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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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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines by Lelisa Wogi, Amruth Thelkar, Tesfabirhan Shoga Tahiro, Tadele Ayana, Shabana Urooj, Samia Larguech

“…This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
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Opportunistic spectrum sharing protocol and optimal resource allocation based on OFDM cooperation relaying by Wei-dang LU, Xuan-li WU, Xue-jun SHA, Nai-tong ZHANG

“…An opportunistic spectrum sharing protocol based on OFDM cooperation relaying was proposed.When the primary user experiences weak channel conditions,it could not achieve its target rate.If the cognitive user could help the primary user achieve its target rate,it accessed the pectrum of the primary user in the cooperation way.In this access way,the cognitive user used a fraction of the subcarriers to amplify-and-forward the signal of the primary user,to help the primary user achieve its target rate.And uses the remained subcarriers to transmit its own signal.The resource allocation was analyzed in this cooperation way.An optimal resource allocation algorithm based on dual ethod was proposed,which maximized the rate of the cognitive user while g anteeing the primary user achieve its target rate.If the cognitive user could not help the primary user achieve its target rate,to make use the spectrum efficiently,the cognitive user accessed the spectrum of the primary user in the non-cooperation way,and uses the whole accessed spectrum to transmit its own signal.The simulation demonstrates the efficiency of the proposed spectrum sharing protocol as well as its benefit to both primary and cognitive user.…”
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Hybridization of Galactic Swarm and Evolution Whale Optimization for Global Search Problem by Binh Minh Nguyen, Trung Tran, Thieu Nguyen, Giang Nguyen

“…The works presented in this paper addresses the robust population-based global optimization that is influenced by the simplicity and efficiency principles introduced in two new generation optimization algorithms. …”
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Equitable post-disaster relief distribution: a robust multi-objective multi-stage optimization approach by Sogand Soghrati Ghasbeh, Nadia Pourmohammadzia, Masoud Rabbani

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Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm by S. Bharath, A. Vasuki

“…Unlike traditional methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and standard Crow Search Algorithm (CSA), which suffer from premature convergence and limited adaptability to real-time variations, Reinforcement Learning Enhanced Crow Search Algorithm (RL-CSA) which is proposed in this research work solves network reconfiguration optimization problem and minimize energy losses. …”
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