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 >

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 >

Xu Xu¹, Xiaoteng Wang¹, Haitian Yang¹, Zhenjun Yang², Yiqian He^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1831-1861, 2024, DOI:10.32604/cmes.2024.048199 - 20 May 2024

Abstract The multiscale method provides an effective approach for the numerical analysis of heterogeneous viscoelastic materials by reducing the degree of freedoms (DOFs). A basic framework of the Multiscale Scaled Boundary Finite Element Method (MsSBFEM) was presented in our previous works, but those works only addressed two-dimensional problems. In order to solve more realistic problems, a three-dimensional MsSBFEM is further developed in this article. In the proposed method, the octree SBFEM is used to deal with the three-dimensional calculation for numerical base functions to bridge small and large scales, the three-dimensional image-based analysis can be conveniently… More >

Girika Jyoshna^1,*, Md. Zia Ur Rahman¹, L. Koteswararao²

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3067-3080, 2022, DOI:10.32604/cmc.2022.020160 - 27 September 2021

Abstract In issues like hearing impairment, speech therapy and hearing aids play a major role in reducing the impairment. Removal of noise signals from speech signals is a key task in hearing aids as well as in speech therapy. During the transmission of speech signals, several noise components contaminate the actual speech components. This paper addresses a new adaptive speech enhancement (ASE) method based on a modified version of singular spectrum analysis (MSSA). The MSSA generates a reference signal for ASE and makes the ASE is free from feeding reference component. The MSSA adopts three key… More >

Harshita Patel¹, Dharmendra Singh Rajput^1,*, Ovidiu Petru Stan², Liviu Cristian Miclea²

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 73-89, 2022, DOI:10.32604/cmc.2022.017114 - 07 September 2021

Abstract Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other classes. The Imbalanced distribution of data is a natural occurrence in real world datasets, so needed to be dealt with carefully to get important insights. In case of imbalance in data sets, traditional classifiers have to sacrifice their performances, therefore lead to misclassifications. This paper suggests a weighted nearest neighbor approach in a fuzzy manner to deal with this issue. We have adapted the ‘existing algorithm modification solution’ to learn… More >

Ch. Srinivas^1,*, K. Chandrabhushana Rao²

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1801-1817, 2021, DOI:10.32604/cmc.2021.014981 - 05 February 2021

Abstract In this paper we propose an efficient process of physiological artifact elimination methodology from brain waves (BW), which are also commonly known as electroencephalogram (EEG) signal. In a clinical environment during the acquisition of BW several artifacts contaminates the actual BW component. This leads to inaccurate and ambiguous diagnosis. As the statistical nature of the EEG signal is more non-stationery, adaptive filtering is the more promising method for the process of artifact elimination. In clinical conditions, the conventional adaptive techniques require many numbers of computational operations and leads to data samples overlapping and instability of… More >

Ridvan Saraçoğlu^*, Ahmet Fatih Kazankaya^†

Computer Systems Science and Engineering, Vol.35, No.1, pp. 13-19, 2020, DOI:10.32604/csse.2020.35.013

Abstract The genetic algorithm (GA) is a metaheuristic method which simulates the life cycle and the survival of the fittest in the nature for solving optimization problems. This study aimed to develop enhanced operation by modifying the current GA. This development process includes an adaptation method that contains certain developments and adds a new process to the classic algorithm. Individuals of a population will be trialed to adapt to the current solution of the problem by taking them separately for each generation. With this adaptation method, it is more likely to get better results in a More >

Xiao Zhao¹, Haitian Yang^1,2, Qiang Gao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.74, No.2, pp. 139-160, 2011, DOI:10.3970/cmes.2011.074.139

Abstract A piecewised adaptive algorithm in the time domain is presented to solve the transient convection-diffusion heat transfer problem. By expanding all variables at a time interval, an initial and boundary value problem is decoupled into a series of recursive boundary value problems which can be solved by FEM or other well developed numerical schemes to deal with boundary value problems. A steady computing accuracy can be adaptively maintained via the power increase of the expansion, particularly when the step size varies in the whole computing process. Additionally for the nonlinear cases, there is no requirement More >

M. S. Bapat¹, Y. J. Liu^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.58, No.2, pp. 161-184, 2010, DOI:10.3970/cmes.2010.058.161

Abstract A new definition of the interaction list in the fast multipole method (FMM) is introduced in this paper, which can reduce the moment-to-local (M2L) translations by about 30-40% and therefore improve the efficiency for the FMM. In addition, an adaptive tree structure is investigated, which is potentially more efficient than the oct-tree structure for thin and slender domains as in the case of micro-electro-mechanical systems (MEMS). A combination of the modified interaction list (termed L2 modification in the adaptive fast multipole BEM) and the adaptive tree structure in the fast multipole BEM has been implemented… More >