Fawad Zaman^1,#, Adeel Iqbal^2,#, Bakhtiar Ali¹, Abdul Khader Jilani Saudagar^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2535-2550, 2025, DOI:10.32604/cmes.2025.072638 - 26 November 2025

Abstract Accurate estimation of the Direction-of-Arrival (DoA) of incident plane waves is essential for modern wireless communication, radar, sonar, and localization systems. Precise DoA information enables adaptive beamforming, spatial filtering, and interference mitigation by steering antenna array beams toward desired sources while suppressing unwanted signals. Traditional one-dimensional Uniform Linear Arrays (ULAs) are limited to elevation angle estimation due to geometric constraints, typically within the range [0, π]. To capture full spatial characteristics in environments with multipath and angular spread, joint estimation of both elevation and azimuth angles becomes necessary. However, existing 2D and 3D array geometries… More >

Ahmed El Maloufy, Mohamed Amine Tahiri, Ahmed Bencherqui, Hicham Karmouni, Mhamed Sayyouri^*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5789-5822, 2025, DOI:10.32604/cmc.2025.068885 - 23 October 2025

Abstract In the current digital context, safeguarding copyright is a major issue, particularly for architectural drawings produced by students. These works are frequently the result of innovative academic thinking combining creativity and technical precision. They are particularly vulnerable to the risk of illegal reproduction when disseminated in digital format. This research suggests, for the first time, an innovative approach to copyright protection by embedding a double digital watermark to address this challenge. The solution relies on a synergistic fusion of several sophisticated methods: Krawtchouk Optimized Octonion Moments (OKOM), Quaternion Singular Value Decomposition (QSVD), and Discrete Waveform… 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 >

Manuel J. C. S. Reis^*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3023-3039, 2025, DOI:10.32604/cmc.2025.066390 - 23 September 2025

Abstract The Vehicle Routing Problem with Time Windows (VRPTW) presents a significant challenge in combinatorial optimization, especially under real-world uncertainties such as variable travel times, service durations, and dynamic customer demands. These uncertainties make traditional deterministic models inadequate, often leading to suboptimal or infeasible solutions. To address these challenges, this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms (GA) with Local Search (LS), while incorporating stochastic uncertainty modeling through probabilistic travel times. The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance. This adaptivity enhances the algorithm’s… More >

Anis Ben Ghorbal^1,*, Azedine Grine¹, Marwa M. Eid^2,3,*, El-Sayed M. El-Kenawy^4,5

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2001-2028, 2025, DOI:10.32604/cmes.2025.068212 - 31 August 2025

Abstract Preterm birth remains a leading cause of neonatal complications and highlights the need for early and accurate prediction techniques to improve both fetal and maternal health outcomes. This study introduces a hybrid approach integrating Long Short-Term Memory (LSTM) networks with the Hybrid Greylag Goose and Particle Swarm Optimization (GGPSO) algorithm to optimize preterm birth classification using Electrohysterogram signals. The dataset consists of 58 samples of 1000-second-long Electrohysterogram recordings, capturing key physiological features such as contraction patterns, entropy, and statistical variations. Statistical analysis and feature selection methods are applied to identify the most relevant predictors and More > Graphic Abstract

Yuanfei Wei^1,2, Panpan Song³, Qifang Luo^3,4,*, Yongquan Zhou^1,2,3,4

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1235-1265, 2025, DOI:10.32604/cmc.2025.066527 - 29 August 2025

Abstract The combined heat and power economic dispatch (CHPED) problem is a highly intricate energy dispatch challenge that aims to minimize fuel costs while adhering to various constraints. This paper presents a hybrid differential evolution (DE) algorithm combined with an improved equilibrium optimizer (DE-IEO) specifically for the CHPED problem. The DE-IEO incorporates three enhancement strategies: a chaotic mechanism for initializing the population, an improved equilibrium pool strategy, and a quasi-opposite based learning mechanism. These strategies enhance the individual utilization capabilities of the equilibrium optimizer, while differential evolution boosts local exploitation and escape capabilities. The IEO enhances… More >

Wy-Liang Cheng¹, Wei Hong Lim^1,*, Kim Soon Chong¹, Sew Sun Tiang¹, Yit Hong Choo², El-Sayed M. El-kenawy^3,4, Amal H. Alharbi⁵, Marwa M. Eid^6,7

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 2021-2050, 2025, DOI:10.32604/cmc.2025.064243 - 29 August 2025

Abstract The exponential growth of data in recent years has introduced significant challenges in managing high-dimensional datasets, particularly in industrial contexts where efficient data handling and process innovation are critical. Feature selection, an essential step in data-driven process innovation, aims to identify the most relevant features to improve model interpretability, reduce complexity, and enhance predictive accuracy. To address the limitations of existing feature selection methods, this study introduces a novel wrapper-based feature selection framework leveraging the recently proposed Arctic Puffin Optimization (APO) algorithm. Specifically, we incorporate a specialized conversion mechanism to effectively adapt APO from continuous… More >

Jingrui Liu^1,2,*, Zhiwen Hou^1,2, Boyu Wang^1,2, Tianxiang Yin^3,4

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4729-4754, 2025, DOI:10.32604/cmc.2025.066138 - 30 July 2025

Abstract In response to the increasing global energy demand and environmental pollution, microgrids have emerged as an innovative solution by integrating distributed energy resources (DERs), energy storage systems, and loads to improve energy efficiency and reliability. This study proposes a novel hybrid optimization algorithm, DE-HHO, combining differential evolution (DE) and Harris Hawks optimization (HHO) to address microgrid scheduling issues. The proposed method adopts a multi-objective optimization framework that simultaneously minimizes operational costs and environmental impacts. The DE-HHO algorithm demonstrates significant advantages in convergence speed and global search capability through the analysis of wind, solar, micro-gas turbine, 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 >

Nisa Nacar Çıkan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3279-3327, 2025, DOI:10.32604/cmes.2025.065442 - 30 June 2025

Abstract This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks (UPDNs), focusing on the complex 123-Bus test system. Three scenarios are investigated: (1) simultaneous power loss reduction and voltage profile improvement, (2) minimization of voltage and current unbalance indices under various operational cases, and (3) multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index, active power loss, and current unbalance index. Unlike previous research that oftensimplified system components, this work maintains all equipment, including capacitor banks, transformers, and voltage regulators, to ensure realistic results. The study evaluates twelve metaheuristic More >