Zakir Hussain Ahmed^1,*, Maha Ata Al-Furhood², Abdul Khader Jilani Saudagar³, Shakir Khan⁴

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1113-1131, 2024, DOI:10.32604/csse.2024.053574 - 13 September 2024

Abstract The generalized travelling salesman problem (GTSP), a generalization of the well-known travelling salesman problem (TSP), is considered for our study. Since the GTSP is NP-hard and very complex, finding exact solutions is highly expensive, we will develop genetic algorithms (GAs) to obtain heuristic solutions to the problem. In GAs, as the crossover is a very important process, the crossover methods proposed for the traditional TSP could be adapted for the GTSP. The sequential constructive crossover (SCX) and three other operators are adapted to use in GAs to solve the GTSP. The effectiveness of GA using More >

Tianqing Yuan^1,2, Na Li^1,2, Hao Sun³, Sen Tan^4,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4497-4512, 2024, DOI:10.32604/cmc.2024.056061 - 12 September 2024

Abstract To improve the estimation accuracy of state of charge (SOC) and state of health (SOH) for lithium-ion batteries, in this paper, a joint estimation method of SOC and SOH at charging cut-off voltage based on genetic algorithm (GA) combined with back propagation (BP) neural network is proposed, the research addresses the issue of data manipulation resulting from cyber-attacks. Firstly, anomalous data stemming from cyber-attacks are identified and eliminated using the isolated forest algorithm, followed by data restoration. Secondly, the incremental capacity (IC) curve is derived from the restored data using the Kalman filtering algorithm, with… More >

Jiahan He¹, Guangjun Liang^1,2,3,*, Meng Li⁴, Kefan Yao¹, Bixia Wang¹, Lu Li⁵

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3243-3261, 2024, DOI:10.32604/cmc.2024.051710 - 15 August 2024

Abstract In this paper, considering the cost of base station, coverage, call quality, and other practical factors, a multi-objective optimal site planning scheme is proposed. Firstly, based on practical needs, mathematical modeling methods were used to establish mathematical expressions for the three sub-objectives of cost objectives, coverage objectives, and quality objectives. Then, a multi-objective optimization model was established by combining threshold and traffic volume constraints. In order to reduce the time complexity of optimization, a non-dominated sorting genetic algorithm (NSGA) is used to solve the multi-objective optimization problem of site planning. Finally, a strategy for clustering… More >

Wei Zhang¹, Haijun Geng^2,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 427-448, 2024, DOI:10.32604/cmc.2024.051871 - 18 July 2024

Abstract Currently, distributed routing protocols are constrained by offering a single path between any pair of nodes, thereby limiting the potential throughput and overall network performance. This approach not only restricts the flow of data but also makes the network susceptible to failures in case the primary path is disrupted. In contrast, routing protocols that leverage multiple paths within the network offer a more resilient and efficient solution. Multipath routing, as a fundamental concept, surpasses the limitations of traditional shortest path first protocols. It not only redirects traffic to unused resources, effectively mitigating network congestion, but… More >

Jiawei Qin^1,2, Hua Zhang^1,*, Hanbing Yan², Tian Zhu², Song Hu¹, Dingyu Yan²

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 527-544, 2024, DOI:10.32604/iasc.2024.047509 - 11 July 2024

Abstract By the analysis of vulnerabilities of Android native system services, we find that some vulnerabilities are caused by inconsistent data transmission and inconsistent data processing logic between client and server. The existing research cannot find the above two types of vulnerabilities and the test cases of them face the problem of low coverage. In this paper, we propose an extraction method of test cases based on the native system services of the client and design a case construction method that supports multi-parameter mutation based on genetic algorithm and priority strategy. Based on the above method, More >

Jiahui Liu^1,2, Lang Li^1,2,*, Di Li^1,2, Yu Ou^1,2

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4641-4657, 2024, DOI:10.32604/cmc.2024.051613 - 20 June 2024

Abstract Correlation power analysis (CPA) combined with genetic algorithms (GA) now achieves greater attack efficiency and can recover all subkeys simultaneously. However, two issues in GA-based CPA still need to be addressed: key degeneration and slow evolution within populations. These challenges significantly hinder key recovery efforts. This paper proposes a screening correlation power analysis framework combined with a genetic algorithm, named SFGA-CPA, to address these issues. SFGA-CPA introduces three operations designed to exploit CPA characteristics: propagative operation, constrained crossover, and constrained mutation. Firstly, the propagative operation accelerates population evolution by maximizing the number of correct bytes… More >

Djeldjli Halima^1,*, Benatiallah Djelloul¹, Ghasri Mehdi², Tanougast Camel³, Benatiallah Ali⁴, Benabdelkrim Bouchra¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4725-4740, 2024, DOI:10.32604/cmc.2024.051002 - 20 June 2024

Abstract When designing solar systems and assessing the effectiveness of their many uses, estimating sun irradiance is a crucial first step. This study examined three approaches (ANN, GA-ANN, and ANFIS) for estimating daily global solar radiation (GSR) in the south of Algeria: Adrar, Ouargla, and Bechar. The proposed hybrid GA-ANN model, based on genetic algorithm-based optimization, was developed to improve the ANN model. The GA-ANN and ANFIS models performed better than the standalone ANN-based model, with GA-ANN being better suited for forecasting in all sites, and it performed the best with the best values in the… More > Graphic Abstract

Junqing Bai¹, Qiuchao Dai^1,*, Yingying Li²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5083-5103, 2024, DOI:10.32604/cmc.2024.050921 - 20 June 2024

Abstract To support the explosive growth of Information and Communications Technology (ICT), Mobile Edge Computing (MEC) provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge. However, resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications. To address the difficulty of running computationally intensive applications on resource-constrained clients, a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper. Then a user benefit function EoU (Experience of Users) is… More >

Abdulelah Alwabel^1,*, Chinmaya Kumar Swain²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4127-4148, 2024, DOI:10.32604/cmc.2024.048833 - 20 June 2024

Abstract Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources. However, the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes, thus making the application placement problem more complex than that in cloud computing. An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the… More >

Chao-Lung Yang^1,*, Melkamu Mengistnew Teshome¹, Yu-Zhen Yeh¹, Tamrat Yifter Meles²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3519-3547, 2024, DOI:10.32604/cmc.2024.048462 - 20 June 2024

Abstract In this study, we introduce a novel multi-objective optimization model tailored for modern manufacturing, aiming to mitigate the cost impacts of operational disruptions through optimized corrective maintenance. Central to our approach is the strategic placement of maintenance stations and the efficient allocation of personnel, addressing a crucial gap in the integration of maintenance personnel dispatching and station selection. Our model uniquely combines the spatial distribution of machinery with the expertise of operators to achieve a harmonious balance between maintenance efficiency and cost-effectiveness. The core of our methodology is the NSGA III+ Dispatch, an advanced adaptation… More >