Weiwu Jiang¹, Xiaowei Gao^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 41-76, 2024, DOI:10.32604/cmes.2024.048313

Abstract The collocation method is a widely used numerical method for science and engineering problems governed by partial differential equations. This paper provides a comprehensive review of collocation methods and their applications, focused on elasticity, heat conduction, electromagnetic field analysis, and fluid dynamics. The merits of the collocation method can be attributed to the need for element mesh, simple implementation, high computational efficiency, and ease in handling irregular domain problems since the collocation method is a type of node-based numerical method. Beginning with the fundamental principles of the collocation method, the discretization process in the continuous domain is elucidated, and how… More >

Sharaf Alzoubi¹, Laith Abualigah^{2,3,4,5,6,7,8,*}, Mohamed Sharaf⁹, Mohammad Sh. Daoud¹⁰, Nima Khodadadi¹¹, Heming Jia¹²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2557-2604, 2024, DOI:10.32604/cmes.2023.045170

Abstract This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm (SSOA). The SSOA combines the principles of swarm intelligence and synergistic cooperation to search for optimal solutions efficiently. A synergistic cooperation mechanism is employed, where particles exchange information and learn from each other to improve their search behaviors. This cooperation enhances the exploitation of promising regions in the search space while maintaining exploration capabilities. Furthermore, adaptive mechanisms, such as dynamic parameter adjustment and diversification strategies, are incorporated to balance exploration and exploitation. By leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation, the SSOA… More >

Danial Jahed Armaghani^1,*, Ahmed Salih Mohammed^2,3, Ramesh Murlidhar Bhatawdekar⁴, Pouyan Fakharian⁵, Ashutosh Kainthola⁶, Wael Imad Mahmood⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2023-2027, 2024, DOI:10.32604/cmes.2023.031701

Abstract This article has no abstract. More >

Mudassir Shams¹, Naila Rafiq², Nasreen Kausar³, Nazir Ahmad Mir², Ahmad Alalyani^4,*

Computer Systems Science and Engineering, Vol.42, No.2, pp. 689-701, 2022, DOI:10.32604/csse.2022.022269

Abstract In this study, we construct a family of single root finding method of optimal order four and then generalize this family for estimating of all roots of non-linear equation simultaneously. Convergence analysis proves that the local order of convergence is four in case of single root finding iterative method and six for simultaneous determination of all roots of non-linear equation. Some non-linear equations are taken from physics, chemistry and engineering to present the performance and efficiency of the newly constructed method. Some real world applications are taken from fluid mechanics, i.e., fluid permeability in biogels and biomedical engineering which includes… More >

Andi Tang, Huan Zhou^*, Tong Han, Lei Xie

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 331-364, 2022, DOI:10.32604/cmes.2021.017310

Abstract The sparrow search algorithm (SSA) is a newly proposed meta-heuristic optimization algorithm based on the sparrow foraging principle. Similar to other meta-heuristic algorithms, SSA has problems such as slow convergence speed and difficulty in jumping out of the local optimum. In order to overcome these shortcomings, a chaotic sparrow search algorithm based on logarithmic spiral strategy and adaptive step strategy (CLSSA) is proposed in this paper. Firstly, in order to balance the exploration and exploitation ability of the algorithm, chaotic mapping is introduced to adjust the main parameters of SSA. Secondly, in order to improve the diversity of the population… More >