Mohammed A. El-Shorbagy¹, Anas Bouaouda^2,*, Laith Abualigah^3,4, Fatma A. Hashim^5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2339-2404, 2025, DOI:10.32604/cmes.2025.061028 - 03 March 2025

Abstract With the rapid advancements in technology and science, optimization theory and algorithms have become increasingly important. A wide range of real-world problems is classified as optimization challenges, and meta-heuristic algorithms have shown remarkable effectiveness in solving these challenges across diverse domains, such as machine learning, process control, and engineering design, showcasing their capability to address complex optimization problems. The Stochastic Fractal Search (SFS) algorithm is one of the most popular meta-heuristic optimization methods inspired by the fractal growth patterns of natural materials. Since its introduction by Hamid Salimi in 2015, SFS has garnered significant attention… More >

Abdelazim G. Hussien^1,2, Guoxi Liang³, Huiling Chen^4,*, Haiping Lin^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2267-2289, 2023, DOI:10.32604/cmes.2023.024247 - 09 March 2023

Abstract Many complex optimization problems in the real world can easily fall into local optimality and fail to find the optimal solution, so more new techniques and methods are needed to solve such challenges. Metaheuristic algorithms have received a lot of attention in recent years because of their efficient performance and simple structure. Sine Cosine Algorithm (SCA) is a recent Metaheuristic algorithm that is based on two trigonometric functions Sine & Cosine. However, like all other metaheuristic algorithms, SCA has a slow convergence and may fail in sub-optimal regions. In this study, an enhanced version of More >

Pankaj Kumar Sharma^1,*, Uma Shankar Modani²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1935-1951, 2023, DOI:10.32604/csse.2023.031509 - 03 November 2022

Abstract The mobile transient and sensor network’s routing algorithm detects available multi-hop paths between source and destination nodes. However, some methods are not as reliable or trustworthy as expected. Therefore, finding a reliable method is an important factor in improving communication security. For further enhancement of protected communication, we suggest a trust cluster based secure routing (TCSR) framework for wireless sensor network (WSN) using optimization algorithms. First, we introduce an efficient cluster formation using a modified tug of war optimization (MTWO) algorithm, which provides load-balanced clusters for energy-efficient data transmission. Second, we illustrate the optimal head… More >

Ceren Baştemur Kaya¹, Ebubekir Kaya^2,*, Göksel Gökkuş³

Computer Systems Science and Engineering, Vol.45, No.1, pp. 69-84, 2023, DOI:10.32604/csse.2023.030598 - 16 August 2022

Abstract It is one of the topics that have been studied extensively on maximum power point tracking (MPPT) recently. Traditional or soft computing methods are used for MPPT. Since soft computing approaches are more effective than traditional approaches, studies on MPPT have shifted in this direction. This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT. The meta-heuristic training algorithms used are particle swarm optimization (PSO), harmony search (HS), cuckoo search (CS), artificial bee colony (ABC) algorithm, bee algorithm (BA), differential evolution (DE) and flower pollination algorithm (FPA). The… More >

Lubna Alhenak¹, Manar Hosny^1,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1045-1074, 2019, DOI:10.32604/cmc.2019.08355

Abstract In recent years, the volume of information in digital form has increased tremendously owing to the increased popularity of the World Wide Web. As a result, the use of techniques for extracting useful information from large collections of data, and particularly documents, has become more necessary and challenging. Text clustering is such a technique; it consists in dividing a set of text documents into clusters (groups), so that documents within the same cluster are closely related, whereas documents in different clusters are as different as possible. Clustering depends on measuring the content (i.e., words) of… More >