Differentiable Deep Learning Surrogate Models Applied to the Optimization of the IFMIF-DONES Facility by Galo Gallardo Romero, Guillermo Rodríguez-Llorente, Lucas Magariños Rodríguez, Rodrigo Morant Navascués, Nikita Khvatkin Petrovsky, Rubén Lorenzo Ortega, Roberto Gómez-Espinosa Martín

“…This approach has resulted in models that are able of approximating complex simulations with high accuracy (less than 17% percentage error for the worst case) and significantly reduced inference time (ranging from 2 to 6 orders of magnitude) while being differentiable. The substantial speed-up factors enable the application of online reinforcement learning algorithms, and the differentiable nature of the models allows for seamless integration with differentiable programming techniques, facilitating the solving of inverse problems to find the optimal parameters for a given objective. …”
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OPT-IQA: Automated camera parameters tuning framework with IQA-guided optimization by Jan-Henner Roberg, Vladyslav Mosiichuk, Ricardo Silva, Luís Rosado

“…It also facilitates the seamless integration of supplementary IQA metrics and optimization algorithms to support additional use cases. …”
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Electrical discharge machining: Recent advances and future trends in modeling, optimization, and sustainability by Muhamad Taufik Ulhakim, Sukarman, Khoirudin, Dodi Mulyadi, Hendri Susilo, Rohman, Muji Setiyo

“…Advanced modeling techniques, such as finite element analysis (FEA) and artificial intelligence (AI)-driven simulations, have improved the accuracy of process predictions, enabling real-time adjustments and precise control of machining parameters. Optimization approaches, including machine learning-based algorithms, multi-objective optimization, and hybrid methods, have enhanced key performance indicators, such as material removal rate (MRR), surface quality, and tool wear, thereby increasing process efficiency and reducing machining time. …”
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Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…This study presents a novel integrated framework for the structural analysis and optimization of multi-floor buildings by combining validated theoretical models with machine learning and evolutionary algorithms. …”
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Optimisation tools for meeting nutrient requirements of Indian children and adults at optimal cost by Fathima Ayoob, Jawahar R. Manivannan, Ashikh Ahmed, Afsal K. Murikkanchery, Abhishek Kumar, Santu Ghosh, Patrick Webb, Anura V. Kurpad, Tinku Thomas

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An Information-Extreme Algorithm for Universal Nuclear Feature-Driven Automated Classification of Breast Cancer Cells by Taras Savchenko, Ruslana Lakhtaryna, Anastasiia Denysenko, Anatoliy Dovbysh, Sarah E. Coupland, Roman Moskalenko

“…These features were then used to classify cells as normal or malignant using an information-extreme algorithm. This algorithm optimizes an information criterion within a binary Hamming space to achieve robust recognition with minimal input features. …”
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ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

“…This paper proposes a novel improved crisscross optimization (ICSO) algorithm, a hybrid evolutionary approach that integrates crisscross optimization and perturbation mechanisms to find the suitable latent vector. …”
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Enhanced MPP Tracking in Partial Shading Conditions for Solar PV Systems: A Metaheuristic Approach Utilizing Projectile Search Algorithm by Md Tahmid Hussain, Mohammed Shahabuddin, Liang-Yin Huang, Adil Sarwar, Mohammed Asim, Shafiq Ahmad, Hwa-Dong Liu, Mohd Tariq

“…Addressing the need for effective Maximum Power Point (MPP) capture in diverse partial shading scenarios, this study introduces a novel MPPT technique based on the Projectile Search Algorithm (PSA). The PSA, inspired by the projectile motion of physical objects, is a metaheuristic optimization algorithm tailored for solving optimization problems by simulating projectile motion within a search space to identify optimal solutions. …”
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Double layered expansion planning for virtual power plants considering virtual energy storage systems by Jianghai Ma, Xuanwen Gu, Yao Zhang, Jinming Gu, Wenjie Luo, Feng Gao

“…To improve computational efficiency, a hybrid Grey Wolf Optimization algorithm is employed for model solution. …”
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Mitigating Dead Node Impact on Coverage and Connectivity in Wireless Sensor Networks Using a Hybrid Approach by Omeed K. Khorsheed

“…The ABC algorithm adjusts sensor node placement to maximize the coverage and minimize holes, while the SRCA algorithm restores connectivity by reconnecting the network when nodes fail. …”
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Energy management for microgrids integrating renewable sources and hybrid electric vehicles by Wanying Liu, Chunqing Rui, Zilin Liu, Jinxin Chen

“…It also incorporates demand response mechanisms for greater resilience. The Kepler Optimization Algorithm (KOA), inspired by Kepler's laws of planetary motion, is employed to tackle the nonlinear optimization problem. …”
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A novel interval prediction method in wind speed based on deep learning and combination prediction by XueJun Chen, Tao Han, Peng Cheng, Xuanfang Da

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The Equal-Time Waypoint Method: A Multi-AUV Path Planning Approach That Is Based on Velocity Variation by Chenxin Yin, Kai Shi, Hailong Wang

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An improved catastrophe progression method based on HMSLGWO–AHP for grouting quality assessment by Yushan Zhu, Zhu Yang, Ning Li, Jian Huang

“…Subsequently, the analytic hierarchy process (AHP) method improved by the hierarchical multi‐strategy learning gray wolf optimization (HMSLGWO) algorithm is employed to determine the relative significance of indices, in which, the HMSLGWO algorithm, augmented by Gaussian mixture model clustering and multi‐strategy learning, optimizes the consistency of the AHP judgment matrix. …”
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An overview of distributed economic dispatch of microgrids: advances and challenges by Lei Sun, Wenjing An, Yangkai Chen, Peifeng Zhao, Derui Ding

“…Economic dispatch (ED) is necessary to achieve optimal power allocation while meeting practical physical constraints and ensuring economic benefits and production safety. …”
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WSNetDefender: Securing Wireless Sensor Networks Using BBIDNet and Fuzzy-DQN Threat Mitigation System (FD-TMS) by Mohammed A. Aleisa

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Integrating Large Language Models and Optimization in Semi- Structured Decision Making: Methodology and a Case Study by Gianpaolo Ghiani, Gianluca Solazzo, Gianluca Elia

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A PSO-Based Approach for the Optimal Allocation of Electric Vehicle Parking Lots to the Electricity Distribution Network by Marzieh Sadat Arabi, Anjali Awasthi

“…Using the particle swarm optimization (PSO) algorithm, the study maximizes total benefits, taking into account network parameters, vehicle data, and market prices. …”
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Multi-objective optimization of design parameters for tractor hydro-mechanical continuously variable transmissions by Zhen Zhu, Rui Hou, Hongwei Zhang, Dehai Wang, Long Chen

“…In this paper, an independently designed hydro-mechanical CVT transmission is taken as the research object, and the transmission design parameters are optimized based on the tractor’s whole life-cycle speed usage rate, and the Multi-Objective Genetic Algorithm(MOGA) is used for optimization and solution. …”
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A Rapid Convex Programming Method for Air-to-Air Missile Trajectory Based on Improved Trust-Region Algorithm by Zeng Yuwen, Zhang Huijun, Liao Xueyang

“…Aiming at the shortcomings of traditional guidance laws for air-to-air missiles in handling multiple nonlinear constraints during the mid-course guidance, this paper proposes an optimization method for mid-course guidance trajectory using sequential convex programming (SCP), and designs an improved trust-region algorithm to enhance the convergence performance of the optimization. …”
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