A Self-Learning Hyper-Heuristic Algorithm Based on a Genetic Algorithm: A Case Study on Prefabricated Modular Cabin Unit Logistics Scheduling in a Cruise Ship Manufacturer by Jinghua Li, Ruipu Dong, Xiaoyuan Wu, Wenhao Huang, Pengfei Lin

“…The GA-SLHH employs a genetic algorithm combined with a self-learning strategy as its high-level strategy (HLS), optimizing low-level heuristics (LLHs) while uncovering potential relationships between adjacent decision-making stages. …”
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Hydrogen Production Using PVs with MPPT Optimization by Kristián Ondrejička, Vladimír Goga, Šimon Berta, Michal Miloslav Uličný, Vladimír Kutiš

“…This study aims to enhance green hydrogen production by optimizing PV-PEMEL performance using commercial power electronics, while improving energy storage and reducing costs for sustainable hydrogen generation.…”
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Portfolio optimization with MOPSO-Shrinkage hybrid model by Minh Tran, Nhat M. Nguyen

“…This paper introduces a novel framework for portfolio optimization that integrates Multi-Objective Particle Swarm Optimization (MOPSO) with shrinkage covariance estimators, referred to as the MOPSO-Shrinkage hybrid model. …”
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Synthesis of Thinned Concentric Circular Antenna Arrays Using Modified TLBO Algorithm by Zailei Luo, Xueming He, Xuedong Chen, Xin Luo, Xiaoqing Li

“…Teaching-learning-based optimization (TLBO) algorithm is a new kind of stochastic metaheuristic algorithm which has been proven effective and powerful in many engineering optimization problems. …”
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A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling by Ruochen Liu, Chenlin Ma, Wenping Ma, Yangyang Li

“…The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. …”
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Enhanced Anti-Lock Braking System Performance: A Comparative Study of Adaptive Terminal Sliding Mode Control Approaches by Salma Khatory, Houcine Chafouk, El Mehdi Mellouli

“…Gain tuning, essential for optimizing system performance and reducing tracking errors, is achieved using the efficient Teaching–Learning-Based Optimization (TLBO) algorithm. …”
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Energy scheduling algorithm for urban rail active traction power supply system by ZHANG Chao, LI Hongbo, ZHAO Liying, HUANG Zihao, LUO Wenguang, WANG Xiong

“…The full power and constant voltage models were used to simulate the two different working conditions of the bidirectional converter, and the internal and external double-layer iterative algorithm was used to calculate the power flow. When all the bidirectional converters were in constant voltage mode, the minimum energy consumption of the whole network was taken to solve the output voltage equation of the traction substation and optimization model of inequation constraints. …”
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Dance Motion Capture Based on Data Fusion Algorithm and Wearable Sensor Network by Yueru Li

“…In this paper, a sensor-body coordinate system calibration algorithm based on hand-eye calibration is proposed, which only requires three calibration poses to complete the calibration of the whole-body sensor-body coordinate system. …”
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Enhanced Cuckoo Search Optimization with Opposition-Based Learning for the Optimal Placement of Sensor Nodes and Enhanced Network Coverage in Wireless Sensor Networks by Mandli Rami Reddy, M. L. Ravi Chandra, Ravilla Dilli

“…The resource and energy constraints of sensor nodes, operational conditions, and network size pose challenges to the optimal coverage of targets in the region of interest (ROI). …”
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Hybrid genetic algorithm and deep learning techniques for advanced side-channel attacks by Faisal Hameed, Hoda Alkhzaimi

“…These findings validate genetic algorithms as a robust alternative for optimizing side-channel attack models, offering both scalability and consistent performance across diverse attack scenarios while advancing the state of cryptographic security assessment.…”
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Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system performance enhancement and protection adaptation by Nasreddine Bouchikhi, Fethi Boussadia, Riyadh Bouddou, Ayodeji Olalekan Salau, Saad Mekhilef, Chaima Gouder, Sarra Adiche, Abdallah Belabbes

“…This paper presents a hybrid technique that integrates a modified grey wolf optimization (MGWO) algorithm, implemented in MATLAB, with the electrical transient and analysis program (ETAP) software for security analysis to achieve the optimal locations and sizing of DG units under protection adaptation. …”
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RESEARCH ON DYNAMIC PERFORMANCE OF GEAR SYSTEM BASED ON ORTHOGONAL DESIGN AND GENETIC ALGORITHM by WU ZhengWei, WU XunCheng, ZHANG JueCheng

“…Dynamic performance of gear system especially vibration was a typical nonlinear problem,while the vibration was closely related to the gear profile modification,the solving gear profile modification parameters was a nonlinear optimization problem. …”
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Bio inspired feature selection and graph learning for sepsis risk stratification by D. Siri, Raviteja Kocherla, Sudharshan Tumkunta, Pamula Udayaraju, Krishna Chaitanya Gogineni, Gowtham Mamidisetti, Nanditha Boddu

“…Using the MIMIC-IV dataset, we employ the Wolverine Optimization Algorithm (WoOA) to select clinically relevant features, followed by a Generative Pre-Training Graph Neural Network (GPT-GNN) that models complex patient relationships through self-supervised learning. …”
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An Enhanced Bio-inspired GWO–DE Technique for Efficient Feature Selection in the EEG-RSVP Paradigm by S. Abinayaa, S. S. Sridhar

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A Detailed Comparison of Two New Heuristic Algorithms Based on Gazelles Behavior by Emine Baş

“…In this study, Mountain Gazelle Optimization (MGO) and Gazelle Optimization Algorithm (GOA) algorithms, which have been newly proposed in recent years, were examined. …”
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Sustainable closed-loop supply chain network design: heuristic hybrid approach with considering inflation and carbon emission policies by Saeid Kalantari, Hamed Kazemipoor, Farzad Movahedi Sobhani, Seyyed Mohammad Hadji Molana

“…This study aims to decide on operational and tactical levels to configure the Stable Closed Chain Supply Chain Network (SCLSC) to maximize Net Present Value (NPV) and seek to minimize carbon emissions while maintaining environmentally friendly policies and considering inflation.Methodology: This paper considers a solid Fuzzy Robust Optimization (FRO) approach to deal with stable, closed-loop supply chain uncertainties. …”
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Multi-AGV multitask collaborative scheduling based on an improved ant colony algorithm by Yazhen Zhu, Qing Song, Meng Li

“…Existing research mainly focuses on the optimization of automated guided vehicle (AGV) path planning and scheduling, emphasizing on the minimization of conflicts and deadlocks, multi-objective task scheduling, and metaheuristic algorithm optimization, while ignoring path stability and real-time path planning in dynamic environments. …”
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Leveraging the Louvain algorithm for enhanced group formation and collaboration in online learning environments by Minkyung Lee, Priya Sharma

“…Abstract This study explores the dynamics of student interaction networks within an online asynchronous discussion forum, focusing on both whole group discussions and subgroup interactions distinguished by the Louvain algorithm, a renowned community detection method. …”
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Design of digital low-carbon system for smart buildings based on PPO algorithm by Yaohuan Wu, Nan Xie

“…The research results indicate that improving the near-end strategy optimization algorithm can reduce carbon emissions by 2354CO2e, while the lowest operating cost of the model is only 35,000 yuan. …”
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Syn-MolOpt: a synthesis planning-driven molecular optimization method using data-derived functional reaction templates by Xiaodan Yin, Xiaorui Wang, Zhenxing Wu, Qin Li, Yu Kang, Yafeng Deng, Pei Luo, Huanxiang Liu, Guqin Shi, Zheng Wang, Xiaojun Yao, Chang-Yu Hsieh, Tingjun Hou

“…Although many deep-learning-based molecular optimization algorithms have been proposed and may perform well on benchmarks, they usually do not pay sufficient attention to the synthesizability of molecules, resulting in optimized compounds difficult to be synthesized. …”
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