Weicong Tan^1,#, Qiwu Wu^2,3,#,*, Lingzhi Jiang¹, Tao Tong², Yunchen Su²

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3621-3652, 2025, DOI:10.32604/cmc.2025.068781 - 23 September 2025

Abstract This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization and multi-strategy fusion (BFDBO), which is designed to tackle the complexities associated with multi-UAV collaborative trajectory planning in intricate battlefield environments. Initially, a collaborative planning cost function for the multi-UAV system is formulated, thereby converting the trajectory planning challenge into an optimization problem. Building on the foundational dung beetle optimization (DBO) algorithm, BFDBO incorporates three significant innovations: a boundary reflection mechanism, an adaptive mixed exploration strategy, and a dynamic multi-scale mutation strategy. These enhancements are intended to… More >

Tayfun Abut^*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 4023-4042, 2025, DOI:10.32604/cmc.2025.066920 - 23 September 2025

Abstract In this study, a dynamic model for an inverted pendulum system (IPS) attached to a car is created, and two different control methods are applied to control the system. The designed control algorithms aim to stabilize the pendulum arms in the upright position and the car to reach the equilibrium position. Grey Wolf Optimization-based Linear Quadratic Regulator (GWO-LQR) and GWO-based Fuzzy LQR (FLQR) control algorithms are used in the control process. To improve the performance of the LQR and FLQR methods, the optimum values of the coefficients corresponding to the foot points of the membership… More >

Raja Masadeh¹, Omar Almomani^2,*, Abdullah Zaqebah¹, Shayma Masadeh³, Kholoud Alshqurat³, Ahmad Sharieh⁴, Nesreen Alsharman⁵

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3709-3737, 2025, DOI:10.32604/cmc.2025.066797 - 23 September 2025

Abstract This research presents a novel nature-inspired metaheuristic optimization algorithm, called the Narwhale Optimization Algorithm (NWOA). The algorithm draws inspiration from the foraging and prey-hunting strategies of narwhals, “unicorns of the sea”, particularly the use of their distinctive spiral tusks, which play significant roles in hunting, searching prey, navigation, echolocation, and complex social interaction. Particularly, the NWOA imitates the foraging strategies and techniques of narwhals when hunting for prey but focuses mainly on the cooperative and exploratory behavior shown during group hunting and in the use of their tusks in sensing and locating prey under the… 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 >

Essam H. Houssein^1,*, Eman Saber¹, Nagwan Abdel Samee²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2445-2480, 2025, DOI:10.32604/cmes.2025.069184 - 31 August 2025

Abstract The diagnosis of Dry Eye Disease (DED), however, usually depends on clinical information and complex, high-dimensional datasets. To improve the performance of classification models, this paper proposes a Computer Aided Design (CAD) system that presents a new method for DED classification called (IAOO-PSO), which is a powerful Feature Selection technique (FS) that integrates with Opposition-Based Learning (OBL) and Particle Swarm Optimization (PSO). We improve the speed of convergence with the PSO algorithm and the exploration with the IAOO algorithm. The IAOO is demonstrated to possess superior global optimization capabilities, as validated on the IEEE Congress on More >

Kamepalli S. L. Prasanna¹, Vijaya J², Parvathaneni Naga Srinivasu¹, Babar Shah³, Farman Ali^4,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1603-1630, 2025, DOI:10.32604/cmc.2025.068707 - 29 August 2025

Abstract Cardiovascular disease prediction is a significant area of research in healthcare management systems (HMS). We will only be able to reduce the number of deaths if we anticipate cardiac problems in advance. The existing heart disease detection systems using machine learning have not yet produced sufficient results due to the reliance on available data. We present Clustered Butterfly Optimization Techniques (RoughK-means+BOA) as a new hybrid method for predicting heart disease. This method comprises two phases: clustering data using Roughk-means (RKM) and data analysis using the butterfly optimization algorithm (BOA). The benchmark dataset from the UCI More >

P. William^1,2, Ved Prakash Mishra¹, Osamah Ibrahim Khalaf^3,*, Arvind Mukundan⁴, Yogeesh N⁵, Riya Karmakar⁶

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5133-5156, 2025, DOI:10.32604/cmc.2025.065840 - 30 July 2025

Abstract Cloud computing has become an essential technology for the management and processing of large datasets, offering scalability, high availability, and fault tolerance. However, optimizing data replication across multiple data centers poses a significant challenge, especially when balancing opposing goals such as latency, storage costs, energy consumption, and network efficiency. This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization (DMGO), designed to enhance data replication efficiency in cloud environments. Unlike traditional static replication systems, DMGO adapts dynamically to variations in network conditions, system demand, and resource availability. The approach utilizes multi-objective optimization 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 >

Geetanjali Dei^1,2, Deepak Kumar Gupta¹, Binod Kumar Sahu², Amitkumar V. Jha³, Bhargav Appasani^3,*, Nicu Bizon^4,5,*

Energy Engineering, Vol.122, No.8, pp. 3399-3431, 2025, DOI:10.32604/ee.2025.067357 - 24 July 2025

Abstract This paper presents an innovative and effective control strategy tailored for a deregulated, diversified energy system involving multiple interconnected area. Each area integrates a unique mix of power generation technologies: Area 1 combines thermal, hydro, and distributed generation; Area 2 utilizes a blend of thermal units, distributed solar technologies (DST), and hydro power; and Third control area hosts geothermal power station alongside thermal power generation unit and hydropower units. The suggested control system employs a multi-layered approach, featuring a blended methodology utilizing the Tilted Integral Derivative controller (TID) and the Fractional-Order Integral method to enhance… 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 >