COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization by Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qi, Jack Xin, Xin Li, Penghang Yin

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Optimal Coordination of Directional Overcurrent Relays Using an Innovative Fractional-Order Derivative War Algorithm by Bakht Muhammad Khan, Abdul Wadood, Herie Park, Shahbaz Khan, Husan Ali

“…This innovative approach integrates the principles of fractional calculus (FC) into the conventional war optimization (WO) algorithm, significantly improving its optimization properties. …”
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Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike by Hojat Karami, Alireza Rezaei, Amin Atarodi

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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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Multi-Objective Optimization for the Low-Carbon Operation of Integrated Energy Systems Based on an Improved Genetic Algorithm by Yao Duan, Chong Gao, Zhiheng Xu, Songyan Ren, Donghong Wu

“…This paper proposes an improved genetic algorithm (IGA) designed to optimize the multi-objective low-carbon operations of IESs, aiming to minimize both operating costs and carbon emissions. …”
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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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Enhanced skill optimization algorithm: Solution to the stochastic reactive power dispatch framework with optimal inclusion of renewable resources using large‐scale network by Noor Habib Khan, Yong Wang, Raheela Jamal, Sheeraz Iqbal, Mohamed Ebeed, Yazeed Yasin Ghadi, Z. M. S. Elbarbary

“…The normal, lognormal, and Weibull distributions are utilized to model system uncertainties, while Monte‐Carlo simulation and reduction‐based approaches are utilized to generate the novel set of optimal scenarios. …”
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A Markov decision optimization of medical service resources for two-class patient queues in emergency departments via particle swarm optimization algorithm by Chia-Hung Wang, Rong Tian, Kun Hu, Yu-Tin Chen, Tien-Hsiung Ku

“…The particle swarm optimization algorithm was applied to determine the optimal number of servers, service rate, and number of beds. …”
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Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach With Particle Swarm Optimization and Genetic Algorithm by Haitham ELwahsh, Ali Bakhiet, Omar Ibrahim Alirr, Tarek Khalifa, Maazen Alsabaan, Mohamed I. Ibrahem, Engy El-Shafeiy

“…It is recommended that the combined application of PSO for feature reduction and GA for model optimization can be successfully used for improving accuracy rate of such algorithms while reducing computation time. …”
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Multi-strategy enterprise development optimizer for numerical optimization and constrained problems by Xinyu Cai, Weibin Wang, Yijiang Wang

“…However, the analysis of the EDO algorithm shows that it suffers from the defects of rapidly decreasing population diversity and weak exploitation ability when dealing with complex optimization problems, while its algorithmic structure has room for further enhancement in the optimization process. …”
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Optimization of the Mechanical Property of Friction Stir Welded Heat Treatable Aluminum Alloy by using Bio-Inspired Artificial Intelligence Algorithms by Akshansh Mishra, Anish Dasgupta

“…The main objective of the work is to obtain the maximum optimized Ultimate Tensile Strength (MPa) by using Bio-Inspired Artificial Intelligence Algorithms i.e., Differential Evolution and Max Lipschitz optimization (Max LIPO) Algorithm. …”
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Optimization of the Mechanical Property of Friction Stir Welded Heat Treatable Aluminum Alloy by using Bio-Inspired Artificial Intelligence Algorithms by Akshansh Mishra, Anish Dasgupta

“…The main objective of the work is to obtain the maximum optimized Ultimate Tensile Strength (MPa) by using Bio-Inspired Artificial Intelligence Algorithms i.e., Differential Evolution and Max Lipschitz optimization (Max LIPO) Algorithm. …”
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A Chemistry-Based Optimization Algorithm for Quality of Service-Aware Multi-Cloud Service Compositions by Mona Aldakheel, Heba Kurdi

“…These results validate the proposed approach’s effectiveness in optimizing service composition while minimizing computational overhead in multi-cloud environments.…”
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Real-Time Drilling Performance Optimization Using Automated Penetration Rate Algorithms with Vibration Control by Dan Sui

“…Automation has transformed process optimization across industries by enhancing efficiency, safety, and reliability while minimizing human intervention. …”
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DGA-ACO: Enhanced Dynamic Genetic Algorithm—Ant Colony Optimization Path Planning for Agribots by Zhenpeng Zhang, Pengyu Li, Shanglei Chai, Yukang Cui, Yibin Tian

“…A multi-objective fitness function simultaneously optimizes path length, energy efficiency, and safety metrics, while genetic operators prevent algorithmic stagnation. …”
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Optimizing stochastic multi-project scheduling with a simulation integrated multi-objective genetic algorithm by Mudassar Rauf, Muhammad Imran, Jabir Mumtaz, Saima Javed

“…The effectiveness of the proposed SIHMO-GA is evaluated through a real-world case study by comparing it with simulation-optimization approaches, namely the multi-objective genetic algorithm (MOGA) and goal attainment programming. …”
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Spatiotemporally Combined Dimensionality Reduction Algorithm for Optimizing Long-term Operation of Multi-reservoir Systems by CHEN Jia, ZHANG Hanjun, XU Nan

“…To alleviate the “curse of dimensionality” and improve the solution efficiency while ensuring the quality of solutions in optimizing the operation of multi-reservoir systems,this paper proposes a spatiotemporally combined dimensionality reduction algorithm which integrates and improves the dynamic programming with successive approximation (DPSA) and the progressive optimality algorithm (POA).First,a chain-based successive approximation strategy is proposed to expand the DPSA's optimization mode from “single reservoir alternation” to “cascade reservoir chain alternation”,which makes up for the DPSA's shortcomings in dealing with the hydraulic coupling relationships among cascade reservoirs.Then,a dynamic variable decoupling strategy and perturbation mechanism are proposed to deal with the POA's blind search problem and dimensionality problem.Finally,the two improved algorithms are combined,in which the improved POA is applied to solving the optimization problems of cascade reservoir chains under the framework of the improved DPSA.The power generation operation problem of the cascade reservoirs in the Yuan River Basin of Hunan Province and the classical ten-reservoir problem are utilized to test the performance of the proposed algorithm.The proposed algorithm outperforms seven existing alternatives in terms of solution quality and efficiency.The results indicate that the proposed algorithm can effectively alleviate the “curse of dimensionality” in optimizing the operation of multi-reservoir systems,improve the efficiency while ensuring the quality of solutions and has potential to be applied to optimizing the operation of complex large-scale multi-reservoir systems.…”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…While numerous algorithms exist for protein-ligand docking, achieving an optimal balance between accuracy and computational speed remains challenging. …”
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QELPS Algorithm: A Novel Dynamic Optimization Technology for Quantum Circuits Scheduling Engineering Problems by Zuoqiang Du, Xingjie Li, Hui Li

“…We propose a collaborative optimization framework that integrates the Quantum Exchange Lock Parallel Scheduler (QELPS) with the Full-level Joint Optimization SWAP Algorithm (FJOSA). …”
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Learning-Driven Algorithm With Dual Evolution Patterns for Solving Large-Scale Multiobjective Optimization Problems by Mingshuo Song, Wei Song, Khin Wee Lai

“…Recently, a series of evolutionary algorithms have been proposed to enhance the search efficiency when handling large-scale multiobjective optimization problems (LSMOPs). …”
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