State information-driven surrogate-assisted differential evolution for computationally expensive constrained optimization problems by Zihua Zhu, Zan Yang, Zhiyong Liu, Liming Chen, Xiwen Cai

“…Abstract In this paper, a state information-driven surrogate-assisted differential evolution called SI-SADE is proposed for solving expensive constrained optimization problems, in which both the population state and adaptive search mechanism are respectively evaluated and designed based on the feasibility and state information. …”
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Quantum Selection for Genetic Algorithms Applied to Electromagnetic Design Problems by Gabriel F. Martinez, Alessandro Niccolai, Eleonora L. Zich, Riccardo E. Zich

“…The method described in this work proposes a hybrid quantum–classical evolutionary optimization algorithm targeting high-frequency electromagnetic problems. …”
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Design of a general complex problem-solving architecture based on task management and predictive optimization by Shabir Ahmad, Salman Khan, Faisal Jamil, Faiza Qayyum, Abid Ali, DoHyeun Kim

“…The proposed framework makes use of historical data for artificial cognition of the complexity of the given problem. For this, predictive optimization is used, which identifies the problem and intelligently predict the solution based on the given constraints. …”
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QELPS Algorithm: A Novel Dynamic Optimization Technology for Quantum Circuits Scheduling Engineering Problems by Zuoqiang Du, Xingjie Li, Hui Li

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A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

“…Thereby, using the traditional hierarchical economic scheduling method makes it difficult to accurately find the optimal scheduling operating point. To address this problem, this paper proposes a multi-objective dispatch decision-making optimization model for the IMDN with static security region (SSR) constraints. …”
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Optimization Techniques for Physician Scheduling Problem: A Systematic Review of Recent Advancements and Future Directions by Norizal Abdullah, Masri Ayob, Meng Chun Lam, Nasser R. Sabar, Graham Kendall, Mohamad Khairulamirin Md Razali

“…Our study also extends the problem definition, constraints, evaluation functions, and the variants of PSP. …”
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Middle School Students' Approaches to Optimization: Insights into Mathematical Modeling and Real-World Problem Solving by İlayda Mengi, İleyda Arslan, Rüveyda Karaman Dündar

“…This study investigates middle school students' perspectives on optimization problems in mathematics, focusing on their problem-solving processes and learning experiences. …”
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Trajectory Optimization for Non-Prehensile Manipulation of Space Robots by Chen Li, Yayun Wu, Zixuan Zheng

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Optimization of purchasing plans based on forecasted demand for resources by Szymon Niewiadomski, Grzegorz Mzyk

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Reactive Power Optimization Control for Renewable Energy in Distribution Networks Considering Active Power Uncertainties by Jingzhong ZHANG, Fei MENG, Yang SUN, Huixia YU

“…Secondly, in the slope optimization layer, based on the column-and-constraint generation (C&CG) algorithm framework, the main problem model of slope instruction optimization and the sub-problem model of extreme scenarios set filtering are established. …”
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Multi-Strategy-Assisted Hybrid Crayfish-Inspired Optimization Algorithm for Solving Real-World Problems by Wenzhou Lin, Yinghao He, Gang Hu, Chunqiang Zhang

“…At the same time, the performance of ICOA is tested against different high-performance algorithms on 6 engineering optimization examples, 30 high–low-dimension constraint problems and 2 large-scale NP problems. …”
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Stochastic control with state constraints via the Fokker–Planck equation. Application to renewable energy plants with batteries by Bermúdez, Alfredo, Padín, Iago

“…Then, a stochastic control problem with state constraints is introduced and the corresponding optimality conditions involving the Hamilton–Jacobi–Bellman equation are deduced. …”
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Variable Dose-Constraints Method Based on Multiplicative Dynamical Systems for High-Precision Intensity-Modulated Radiation Therapy Planning by Omar M. Abou Al-Ola, Takeshi Kojima, Ryosei Nakada, Norihisa Obata, Kohei Hayashi, Tetsuya Yoshinaga

“…An optimization framework that effectively balances dose–volume constraints and treatment objectives is required in intensity-modulated radiation therapy (IMRT) planning. …”
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Joint Optimization of the 3D Model and 6D Pose for Monocular Pose Estimation by Liangchao Guo, Lin Chen, Qiufu Wang, Zhuo Zhang, Xiaoliang Sun

“…This paper adopts the multi-view geometry constraints within the monocular image sequence to solve the problem. …”
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An effective hybrid decomposition approach to solve the network-constrained stochastic unit commitment problem in large-scale power systems by Ricardo M. Lima, Gonzalo E. Constante-Flores, Antonio J. Conejo, Omar M. Knio

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Minimization of Water Age in Water Distribution Systems under Uncertain Demand by Kristina Korder, Elad Salomons, Avi Ostfeld, Pu Li

“…In cases of low reliability, it is necessary to modify the operating strategy in order to decrease the probability of constraint violation. For this purpose, a chance-constrained optimization problem is formulated, and its benefits for ensuring the user-defined reliability are studied. …”
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Active noise control - a review of control-related problems by Marek PAWEŁCZYK

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Mathematical Modelling Approaches for Integrated Single Machine Scheduling and Electric Vehicle Routing Problem by İclal Bağcı, Hande Öztop, Zeynel Abidin Çil

“…Due to various charging feature constraints, EVRP diverges from the classical vehicle routing problem (VRP) and becomes more complex. …”
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Vehicle Painting Robot Path Planning Using Hierarchical Optimization by Yuya Nagai, Hiromitsu Nakamura, Narito Shinmachi, Yuta Higashizono, Satoshi Ono

“…Therefore, this paper formulates the design of paint paths as a hierarchical optimization problem, where the upper-layer subproblem resembles a vehicle routing problem (VRP), and the lower-layer subproblem involves detailed path planning. …”
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Energy-efficient optimization strategy based on elastic data migration in big data streaming platform by Yonglin PU, Xiaolong XU, Jiong YU, Ziyang LI, Binglei GUO

“…Focused on the problem that the stream computing platform was suffering from the high energy consumption and low efficiency due to the lack of consideration for energy efficiency in designing process, an energy-efficient optimization strategy based on elastic data migration in big data streaming platform (EEDM-BDSP) was proposed.Firstly, models of the load prediction and the resource judgment were set up, and the load prediction algorithm was designed, which predicted the load tendency and determine node resource occupancy, so as to find nodes of resource overload and redundancy.Secondly, models of the resource constraint and the optimal data migration were set up, and the optimal data migration algorithm was proposed, which data migration for the purpose of improving node resource utilization.Finally, model of the energy consumption was set up to calculate the energy consumption saved by the cluster after data migration.The experimental results show that the EEDM-BDSP changes node resources in the cluster can responded on time, the resource utilization and the energy-efficient are improved.…”
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