Comprehensive MILP Formulation and Solution for Simultaneous Scheduling of Machines and AGVs in a Partitioned Flexible Manufacturing System by Cheng Zhuang, Jingbo Qu, Tianyu Wang, Liyong Lin, Youyi Bi, Mian Li

“…The main objective is to numerically optimize the simultaneous scheduling of machines and AGVs while considering various workshop layouts and operational constraints. …”
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HFSA: hybrid feature selection approach to improve medical diagnostic system by Asmaa H. Rabie, Mohammed Aldawsari, Ahmed I. Saleh, M. S. Saraya, Metwally Rashad

“…In FS, chi-square, as a filtering methodology, is applied to quickly select the best features while Hybrid Optimization Algorithm (HOA), as a wrapper methodology, is applied in AS to accurately select features. …”
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Dynamic Stepsize Techniques in DR-Submodular Maximization by Yanfei Li, Min Li, Qian Liu, Yang Zhou

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Achievement of Possibly Maximum Photosynthetic Performances for Multi-Primary Laser Lighting for Indoor Farming by Bingui Lv, Mingkai Huang, Meixue Chen, Liyue Xu, Lihong Lian, Huanting Chen, Yangyu Yao, Jingxuan Sun, Yixuan Lu, Xinqin Liao, Zhong Chen, Ziquan Guo

“…Via reasonably designing the spectral components of artificial lighting sources based on intelligent optimization algorithms such as genetic algorithm (GA), one can readily achieve the maximum photosynthetic luminous efficacy of radiation (PLER), at the same time with good color rendering properties. …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Despite their success, machine learning methods face fundamental limitations in optimizing complex high-dimensional energy landscapes, which motivates research into new methods to improve the robustness and performance of optimization algorithms. …”
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Comparative Evaluation of Traditional and Advanced Algorithms for Photovoltaic Systems in Partial Shading Conditions by Robert Sørensen, Lucian Mihet-Popa

“…This study focuses on the development and comparison of traditional and advanced algorithms, including Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN), for efficient Maximum Power Point Tracking (MPPT). …”
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A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting by Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen

“…Hence, a novel hybrid model is provided, incorporating singular value decomposition (SVD) in conjunction with kernel-based ridge regression (SKRidge), multivariate variational mode decomposition (MVMD), and the light gradient boosting machine (LGBM) as a feature selection method, along with the Runge–Kutta optimization (RUN) algorithm for parameter optimization. …”
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Numerical investigation for optimizing thermal performance of Al2O3-TiO2/water hybrid nanofluid: An artificial neural network approach based on Levenberg–Marquardt algorithm by Khalid Arif, Syed Tauseef Saeed, Talha Anwar, Shajar Abbas, Muhammad Nauman Aslam

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Self-adaptive multi-population quadratic approximation guided jaya optimization applied to economic load dispatch problems with or without valve-point effects by Sukriti Patty, Rajeev Das, Dharmadas Mandal, Provas Kumar Roy

“…This study applies the Self-Adaptive Multi-Population Quadratic Approximation Guided Jaya (SMP-JaQA) algorithm, a state-of-the-art parameter-free optimization technique, to solve the ELD problem effectively. …”
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Investigation of Micro-Scale Damage and Weakening Mechanisms in Rocks Induced by Microwave Radiation and Their Associated Strength Reduction Patterns: Employing Meta-Heuristic Opti... by Zhongyuan Gu, Xin Xiong, Chengye Yang, Miaocong Cao

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Selective opposition based constrained barnacle mating optimization: Theory and applications by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Masuk Abdullah

“…In addition to increasing efficiency by cutting down on wasted time spent exploring, this also increases the likelihood of stumbling onto optimal solutions. After that, it is put through its paces in a real-world case study, where it proves to be superior to the most cutting-edge algorithms available.…”
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Smart wearable sensor-based model for monitoring medication adherence using sheep flock optimization algorithm-attention-based bidirectional long short-term memory (SFOA-Bi-LSTM) by Yasser Alatawi, Palanisamy Amirthalingam, Narmatha Chellamani, Manimurugan Shanmuganathan, Mostafa A. Sayed Ali, Saleh Fahad Alqifari, Vasudevan Mani, Muralikrishnan Dhanasekaran, Abdulelah Saeed Alqahtani, Ahmed Aljabri

“…The data is gathered, preprocessed, and classified to identify MA behavior utilizing the developed DL model known as the sheep flock optimization algorithm-attention-based bidirectional long short-term memory network (SFOA-Bi-LSTM). …”
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Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…The result of Genetic Algorithm analysis also proved the model has converged to the optimal solution effectively, the best solution of X1 = 49.41, X2 = 110.62, X3 = 11.85 and X4 = 20 which gives the maximum removal efficiency = 94.64% of methylene blue. …”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…Additionally, multi-objective optimization solutions are proposed using a Multi-Objective Genetic Algorithm (MOP-GA), which suggest that a comprehensive development strategy that balances urban-rural resource allocation achieves the highest level of integration. …”
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Fractional Order PID Controller Based‐Neural Network Algorithm for LFC in Multi‐Area Power Systems by Ali M. El‐Rifaie, Slim Abid, Ahmed R. Ginidi, Abdullah M. Shaheen

“…The proposed method demonstrates marked improvements over traditional PID controllers and advanced optimization techniques such as Differential Evolution (DE) and Artificial Rabbits Algorithm (ARA). …”
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Risk management strategies for fuel shortages in economic dispatch with multiple fuel options using walrus algorithm by Mahmoud Ibrahim Mohamed, Ali M. Yousef, Ahmed A. Hafez

“…This article comprehensively analyzes the ED process for power plants with multiple fuel options, while achieving multiple objectives: optimizing energy management and boosting supply security. …”
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GIS vibration signal denoising algorithm based on SVD-IACMD by TU Jiayi, GUAN Xiangyu, ZHAO Junyi, LIN Jiangang, LAI Zekai

“…Subsequently, the osprey optimization algorithm (OOA) is used for adaptive modal decomposition of the processed signals, resulting in decomposed intrinsic mode functions (IMF). …”
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Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach by Tomás de Jesús Mateo Sanguino, Jhon Carlos Mendoza Betancourt

“…To this end, we implemented a multiobjective genetic algorithm (MOGA) with the purpose of meeting two simultaneous design objectives, namely, to minimize the number of APs while maximizing the coverage signal over a whole planning area. …”
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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
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Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

“…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
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