A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

“…This paper presents NSGA-III-GKM++, an advanced multi-objective optimization model that integrates the NSGA-III evolutionary algorithm with an enhanced K-means++ clustering technique to improve the convergence speed, solution diversity, and computational efficiency. …”
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Optimizing Long-Term Bank Financial Products Portfolio Problems with a Multiobjective Evolutionary Approach by Jian Xiong, Chao Zhang, Gang Kou, Rui Wang, Hisao Ishibuchi, Fawaz E. Alsaadi

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Optimization design of combustion chamber for a non-road diesel engine in high-altitude region by Yibing Hou, Jun Wang, Jilin Lei, Liang Chen

“…Finally, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to perform multi-objective optimization, and the technique for order preference by similarity to ideal solution (TOPSIS) was utilized to select the optimal combustion chamber structural parameters suitable for high-altitude regions. …”
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Scheduling Optimization of Electric Rubber-Tired Vehicles in Underground Coal Mines Based on Constraint Programming by Maoquan Wan, Hao Li, Hao Wang, Jie Hou

“…This study presents a Constraint Programming (CP)-based optimization framework that integrates Virtual Charging Station Mapping (VCSM) and sensor fusion positioning to decouple spatiotemporal charging conflicts and applies a dynamic topology adjustment algorithm to enhance computational efficiency. …”
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Electromagnetic Analysis and Multi-Objective Design Optimization of a WFSM with Hybrid GOES-NOES Core by Kyeong-Tae Yu, Hwi-Rang Ban, Seong-Won Kim, Jun-Beom Park, Jang-Young Choi, Kyung-Hun Shin

“…Subsequently, a multi-objective optimization was conducted using Latin Hypercube Sampling, meta-modeling, and a genetic algorithm to maximize power density and efficiency while minimizing torque ripple. …”
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Research on Optimization Technology of Minimum Specific Fuel Consumption for Triple-Bypass Variable Cycle Engine by Haonan Guo, Yuhua Zhang, Bing Yu

“…The contribution of each control variable to the engine’s specific fuel consumption was computed using the PSM and, at the same time, due to the linear characteristics of the PSM, it was easy to deal with various constrained linear optimization problems, and the steady-state points with the smallest specific fuel consumption under the constraints could be obtained through the linear optimization algorithm; however, the surge margin and pre-turbine temperature of the optimized point were limited in the optimization process, the method of direct switching inevitably brought the problem of overshoot of the controlled quantity, and the actual controlled quantity could still exceed the safe operation boundary of the engine in the process of change. …”
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Synergizing NOMA and energy harvesting in full duplex mobile edge computing for optimized energy efficiency by Mirza Baber Baig, Taoshen Li, Muhammad Zain Yousaf, Mohit Bajaj, Arvind R. Singh, Milkias Berhanu Tuka

“…The primary objective is to optimize edge computing performance while minimizing energy consumption. …”
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Towards Efficiency and Endurance: Energy–Aerodynamic Co-Optimization for Solar-Powered Micro Air Vehicles by Weicheng Di, Xin Dong, Zixing Wei, Haoji Liu, Zhan Tu, Daochun Li, Jinwu Xiang

“…To address this, this work proposes an automated algorithm for optimal solar panel arrangement on complex upper surfaces of the MAV. …”
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Optimal Allocation Method of Integrated Energy System Considering Joint Operation of Multiple Flexible Resources by DENG Qianwen, LI Qi, QIU Yibin, LI Doumeng, HUO Shasha, CHEN Weirong

“…Then, aimed at the uncertainty of renewable energy output, the optimal clustering number is determined by Elbow method, and typical wind speed scenarios are obtained by K-means clustering algorithm. …”
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Low-noise optimization design for underwater series-connected multi-sphere composite shell structure by Hefan LI, Guanjun ZHANG, Yuzhao KE

“…The radial basis function (RBF) neural network was used to establish a multidimensional mapping model between the design variables and the optimization objective. The particle swarm optimization (PSO) algorithm was employed to optimize the underwater radiation noise of the model, and the results were verified through the finite element method. …”
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Research on Prediction and Optimization of Airport Express Passenger Flow Based on Fusion Intelligence Network Model by Jin He, Yinzhen Li, Yuhong Chao

“…The purpose of this paper is to optimize the accuracy of airport express passenger flow prediction so as to meet the need for the optimal allocation of traffic resources against the background of accelerated urbanization and the rapid development of airport express services. …”
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Long-term electricity demand forecasting of a university campus based on advanced deep learning artificial neural network algorithms by Saad A. Alsamraee, Sanjeev Khanna

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A Hybrid Approach Incorporating WSO-HO and the Newton-Raphson Method to Enhancing Photovoltaic Solar Model Parameters Optimisation by Jeridi Ahmed, Moulahi Mohamed Hedi, Khaterchi Hechmi, Zaafouri Abderrahmen

“…Accurate parameter estimation is vital for optimising the performance and design of photovoltaic (PV) systems. While metaheuristic algorithms (MHAs) offer promising solutions, they often face challenges such as slow convergence and difficulty balancing exploration and exploitation. …”
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Collaborative Optimization of Model Pruning and Knowledge Distillation for Efficient and Lightweight Multi-Behavior Recognition in Piglets by Yizhi Luo, Kai Lin, Zixuan Xiao, Yuankai Chen, Chen Yang, Deqin Xiao

“…In the first stage, the LAMP pruning algorithm is used to prune and optimize redundant channels, resulting in the lightweight YOLOv8-Prune. …”
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Improving air quality prediction using hybrid BPSO with BWAO for feature selection and hyperparameters optimization by Mohamed S. Sawah, Hela Elmannai, Alaa A. El-Bary, Kh. Lotfy, Osama E. Sheta

“…Feature selection (FS) was conducted using Binary version of Grey Wolf Optimizer (BGWO), Particle Swarm Optimization (BPSO), Whale Optimization Algorithm (BWAO), and a novel hybrid BPSO-BWAO approach to identify the most relevant features for AQI prediction. …”
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Advanced Optimization of Flowshop Scheduling with Maintenance, Learning and Deteriorating Effects Leveraging Surrogate Modeling Approaches by Nesrine Touafek, Fatima Benbouzid-Si Tayeb, Asma Ladj, Riyadh Baghdadi

“…We develop and evaluate two distinct strategies for integrating surrogate modeling into the optimization process, leveraging the ABC algorithm. The first strategy uses a Kriging model to dynamically guide the selection of the most effective search operator at each stage of the employed bee phase. …”
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Multi-objective optimization of cushion gas design in underground gas storage using machine learning by Mohaddeseh Ahmadi Aghdam, Maryam Fazaeli, Mahdi Kanaani, Behnam Sedaee

“…This model enabled rapid multi-objective optimization using the MOPSO algorithm. Several Pareto fronts were generated, and the best front provided 500 optimal solutions after 300 iterations. …”
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Optimizing Superior Seed Bunches: A New Approach to Artificial Pollination with Machine Learning Models by Yabani Yabani, Retna Astuti Kuswardani

“… This study aims to optimize oil palm production through the application of more targeted pollination techniques using a data-driven approach and a new optimization model. …”
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Optimizing net-zero energy strategies in airports through a hybrid multi-method framework by Filiz Mizrak, Kagan Cenk Mizrak, Turhan Karakaya

“…The proposed model integrates the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for generating Pareto-optimal solutions, K-Means clustering for classifying strategies, and the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) for prioritizing alternatives under uncertainty. …”
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Optimization Design Scheme for Aerodynamic Noise Reduction in Pantograph Area of High-speed Railway EMU by YU Yongge, WANG Chengtao, GAO Yang, YU Wanyi, MA Changfu, ZHANG Guoqin

“…［Result & Conclusion］ Scheme 4 is identified as the optimal solution. When applied to the CR400BF EMU operating at a speed of 350 km/h, the overall train radiated noise sound pressure level at the nearest standard measuring point to the pantograph is reduced by 0.99 dB(A), while the radiated noise sound pressure level in the pantograph area is reduced by 1.70 dB(A). …”
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