Min Huang¹, Cuichen Zhou¹, Yuming Wang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.085152 - 28 August 2026

Abstract With the complexity of the aviation equipment mission environment, aircraft are inevitably exposed to a high-intensity and stable complex electromagnetic radiation environment for a long time in some mission areas. It is difficult to effectively reduce electromagnetic risk by relying solely on compatible technologies such as electromagnetic shielding and flight path avoidance. Aiming at the problem that aircraft are vulnerable to electromagnetic interference in a harsh electromagnetic environment, this paper proposes an aircraft attitude angle optimization method based on an intelligent optimization algorithm under the framework of digital twin modeling, according to the characteristics that… More >

Zezhong Liu, Jinyu Guo, Xingxu Zhu^*, Junhui Li

Energy Engineering, Vol.123, No.3, 2026, DOI:10.32604/ee.2025.072679 - 27 February 2026

Abstract With the increasing penetration of renewable energy, the coordination of energy storage with thermal power for frequency regulation has become an effective means to enhance grid frequency security. Addressing the challenge of improving the frequency regulation performance of a thermal-storage primary frequency regulation system while reducing its associated losses, this paper proposes a multi-dimensional cooperative optimization strategy for the control parameters of a combined thermal-storage system, considering regulation losses. First, the frequency regulation losses of various components within the thermal power unit are quantified, and a calculation method for energy storage regulation loss is proposed,… More >

Hang Zhou^*, Xiaojun Ding, Song Chen, Qijun Zhang

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1907-1933, 2025, DOI:10.32604/cmes.2025.069198 - 31 August 2025

Abstract Structural Reliability-Based Topology Optimization (RBTO), as an efficient design methodology, serves as a crucial means to ensure the development of modern engineering structures towards high performance, long service life, and high reliability. However, in practical design processes, topology optimization must not only account for the static performance of structures but also consider the impacts of various responses and uncertainties under complex dynamic conditions, which traditional methods often struggle accommodate. Therefore, this study proposes an RBTO framework based on a Kriging-assisted level set function and a novel Dynamic Hybrid Particle Swarm Optimization (DHPSO) algorithm. By leveraging… More >

Thi My Binh Nguyen^#, Thi Hoa Hue Nguyen^#, Thi Ngoc Huyen Do^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5063-5076, 2025, DOI:10.32604/cmc.2025.064610 - 30 July 2025

Abstract Efficient warehouse management is critical for modern supply chain systems, particularly in the era of e-commerce and automation. The Multi-Picker Robot Routing Problem (MPRRP) presents a complex challenge involving the optimization of routes for multiple robots assigned to retrieve items from distinct locations within a warehouse. This study introduces optimized metaheuristic strategies to address MPRRP, with the aim of minimizing travel distances, energy consumption, and order fulfillment time while ensuring operational efficiency. Advanced algorithms, including an enhanced Particle Swarm Optimization (PSO-MPRRP) and a tailored Genetic Algorithm (GA-MPRRP), are specifically designed with customized evolutionary operators to More >

Yuan Zou¹, Chao Lu^1,*, Lvjiang Yin², Xiaoyu Wen³

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2305-2330, 2025, DOI:10.32604/cmc.2025.065972 - 03 July 2025

Abstract The shop scheduling problem with limited buffers has broad applications in real-world production scenarios, so this research direction is of great practical significance. However, there is currently little research on the hybrid flow shop scheduling problem with limited buffers (LBHFSP). This paper deeply investigates the LBHFSP to optimize the goal of the total completion time. To better solve the LBHFSP, a multi-level subpopulation-based particle swarm optimization algorithm (MLPSO) is proposed, which is founded on the attributes of the LBHFSP and the shortcomings of the basic PSO (particle swarm optimization) algorithm. In MLPSO, firstly, considering the… More >

Liang Tang¹, Hongwei Wang¹, Xinyuan Zhu¹, Jiying Liu^2,*, Kaiyue Li^2,*

Energy Engineering, Vol.122, No.6, pp. 2257-2289, 2025, DOI:10.32604/ee.2025.063918 - 29 May 2025

Abstract The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment, hindering the efficient utilization of renewable energy and the low-carbon development of energy systems. To enhance the consumption capacity of green power, the green power system consumption optimization scheduling model (GPS-COSM) is proposed, which comprehensively integrates green power system, electric boiler, combined heat and power unit, thermal energy storage, and electrical energy storage. The optimization objectives are to minimize operating cost, minimize carbon emission, and maximize the consumption of wind and solar curtailment. The multi-objective particle swarm… More >

Sung-Jung Hsiao¹, Wen-Tsai Sung^2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 3891-3905, 2025, DOI:10.32604/cmc.2025.060056 - 06 March 2025

Abstract For optimization algorithms, the most important consideration is their global optimization performance. Our research is conducted with the hope that the algorithm can robustly find the optimal solution to the target problem at a lower computational cost or faster speed. For stochastic optimization algorithms based on population search methods, the search speed and solution quality are always contradictory. Suppose that the random range of the group search is larger; in that case, the probability of the algorithm converging to the global optimal solution is also greater, but the search speed will inevitably slow. The smaller… More >

Xing Wang^1,*, Huazhen Liu¹, Abdelazim G. Hussien², Gang Hu¹, Li Zhang³

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2791-2839, 2025, DOI:10.32604/cmes.2025.058473 - 03 March 2025

Abstract Feature selection (FS) is essential in machine learning (ML) and data mapping by its ability to preprocess high-dimensional data. By selecting a subset of relevant features, feature selection cuts down on the dimension of the data. It excludes irrelevant or surplus features, thus boosting the performance and efficiency of the model. Particle Swarm Optimization (PSO) boasts a streamlined algorithmic framework and exhibits rapid convergence traits. Compared with other algorithms, it incurs reduced computational expenses when tackling high-dimensional datasets. However, PSO faces challenges like inadequate convergence precision. Therefore, regarding FS problems, this paper presents a binary… More >

Shaobo Deng^*, Meiru Xie, Bo Wang, Shuaikun Zhang, Sujie Guan, Min Li

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2723-2751, 2025, DOI:10.32604/cmc.2024.057874 - 17 February 2025

Abstract In recent years, particle swarm optimization (PSO) has received widespread attention in feature selection due to its simplicity and potential for global search. However, in traditional PSO, particles primarily update based on two extreme values: personal best and global best, which limits the diversity of information. Ideally, particles should learn from multiple advantageous particles to enhance interactivity and optimization efficiency. Accordingly, this paper proposes a PSO that simulates the evolutionary dynamics of species survival in mountain peak ecology (PEPSO) for feature selection. Based on the pyramid topology, the algorithm simulates the features of mountain peak… More >

Jiaying Shen¹, Donglin Zhu¹, Yujia Liu², Leyi Wang¹, Jialing Hu¹, Zhaolong Ouyang¹, Changjun Zhou¹, Taiyong Li^3,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 345-369, 2025, DOI:10.32604/cmc.2024.060335 - 03 January 2025

Abstract The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life. The development of the Internet of Things (IoT) relies on the support of base stations, which provide a solid foundation for achieving a more intelligent way of living. In a specific area, achieving higher signal coverage with fewer base stations has become an urgent problem. Therefore, this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization (EPSO)… More >