Guowei Li^1,*, Shujuan Bu², Xinle Yang², Kaijie Liang¹, Zhengri Shao¹, Xiaobei Song¹, Yitian Tang³, Dejing Zong⁴

Energy Engineering, Vol.121, No.12, pp. 3843-3874, 2024, DOI:10.32604/ee.2024.056195 - 22 November 2024

Abstract A novel dual-pressure organic Rankine cycle system (DPORC) with a dual-stage ejector (DE-DPORC) is proposed. The system incorporates a dual-stage ejector that utilizes a small amount of extraction steam from the high-pressure expander to pressurize a large quantity of exhaust gas to perform work for the low-pressure expander. This innovative approach addresses condensing pressure limitations, reduces power consumption during pressurization, minimizes heat loss, and enhances the utilization efficiency of waste heat steam. A thermodynamic model is developed with net output work, thermal efficiency, and exergy efficiency (W_net, η_t, η_ex) as evaluation criteria, an economic model is established… More >

Liang Zeng^1,2,3, Ziyang Ding¹, Junyang Shi¹, Shanshan Wang^1,2,3,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1757-1787, 2024, DOI:10.32604/cmc.2024.055574 - 15 October 2024

Abstract In the manufacturing industry, reasonable scheduling can greatly improve production efficiency, while excessive resource consumption highlights the growing significance of energy conservation in production. This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed (DHPFSP-VPS), considering both the minimum makespan and total energy consumption (TEC) as objectives. A discrete multi-objective squirrel search algorithm (DMSSA) is proposed to solve the DHPFSP-VPS. DMSSA makes four improvements based on the squirrel search algorithm. Firstly, in terms of the population initialization strategy, four hybrid initialization methods targeting different objectives are proposed to enhance… More >

Sayat Ibrayev¹, Batyrkhan Omarov^1,2,3,*, Arman Ibrayeva¹, Zeinel Momynkulov^1,2

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 229-249, 2024, DOI:10.32604/cmc.2024.053075 - 15 October 2024

Abstract This research paper presents a comprehensive investigation into the effectiveness of the DeepSurNet-NSGA II (Deep Surrogate Model-Assisted Non-dominated Sorting Genetic Algorithm II) for solving complex multi-objective optimization problems, with a particular focus on robotic leg-linkage design. The study introduces an innovative approach that integrates deep learning-based surrogate models with the robust Non-dominated Sorting Genetic Algorithm II, aiming to enhance the efficiency and precision of the optimization process. Through a series of empirical experiments and algorithmic analyses, the paper demonstrates a high degree of correlation between solutions generated by the DeepSurNet-NSGA II and those obtained from… More >

Abdulrahman M. Abdulghani^*

Journal on Artificial Intelligence, Vol.6, pp. 241-259, 2024, DOI:10.32604/jai.2024.056259 - 16 October 2024

Abstract Cloud computing has rapidly evolved into a critical technology, seamlessly integrating into various aspects of daily life. As user demand for cloud services continues to surge, the need for efficient virtualization and resource management becomes paramount. At the core of this efficiency lies task scheduling, a complex process that determines how tasks are allocated and executed across cloud resources. While extensive research has been conducted in the area of task scheduling, optimizing multiple objectives simultaneously remains a significant challenge due to the NP (Non-deterministic Polynomial) Complete nature of the problem. This study aims to address… More >

Xiwang Guo¹, Liangbo Zhou¹, Zhiwei Zhang^1,*, Liang Qi^2,*, Jiacun Wang³, Shujin Qin⁴, Jinrui Cao⁵

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4475-4496, 2024, DOI:10.32604/cmc.2024.048123 - 12 September 2024

Abstract This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers. A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time. Based on a product’s AND/OR graph, matrices for task-skill, worker-skill, precedence relationships, and disassembly correlations are developed. A multi-objective discrete chemical reaction optimization algorithm is designed. To enhance solution diversity, improvements are made to four reactions: decomposition, synthesis, intermolecular ineffective collision, and wall invalid collision reaction, completing the evolution of molecular individuals. The established model and improved algorithm are applied to ball 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 >

Xialin Liu^1,2,3,*, Junsheng Wu⁴, Lijun Chen^2,3, Jiyuan Hu⁵

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1601-1631, 2024, DOI:10.32604/cmc.2024.050626 - 18 July 2024

Abstract Virtual machine (VM) consolidation aims to run VMs on the least number of physical machines (PMs). The optimal consolidation significantly reduces energy consumption (EC), quality of service (QoS) in applications, and resource utilization. This paper proposes a prediction-based multi-objective VM consolidation approach to search for the best mapping between VMs and PMs with good timeliness and practical value. We use a hybrid model based on Auto-Regressive Integrated Moving Average (ARIMA) and Support Vector Regression (SVR) (HPAS) as a prediction model and consolidate VMs to PMs based on prediction results by HPAS, aiming at minimizing the More >

Weiwei Zhang¹, Jiaqiang Li¹, Chao Wang², Meng Li³, Zhi Rao^4,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4237-4257, 2024, DOI:10.32604/cmc.2024.050430 - 20 June 2024

Abstract In practical engineering, multi-objective optimization often encounters situations where multiple Pareto sets (PS) in the decision space correspond to the same Pareto front (PF) in the objective space, known as Multi-Modal Multi-Objective Optimization Problems (MMOP). Locating multiple equivalent global PSs poses a significant challenge in real-world applications, especially considering the existence of local PSs. Effectively identifying and locating both global and local PSs is a major challenge. To tackle this issue, we introduce an immune-inspired reproduction strategy designed to produce more offspring in less crowded, promising regions and regulate the number of offspring in areas… More >

Mehrdad Shoeibi¹, Mohammad Mehdi Sharifi Nevisi², Reza Salehi³, Diego Martín^3,*, Zahra Halimi⁴, Sahba Baniasadi⁵

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3469-3493, 2024, DOI:10.32604/cmc.2024.049847 - 20 June 2024

Abstract Hyperspectral (HS) image classification plays a crucial role in numerous areas including remote sensing (RS), agriculture, and the monitoring of the environment. Optimal band selection in HS images is crucial for improving the efficiency and accuracy of image classification. This process involves selecting the most informative spectral bands, which leads to a reduction in data volume. Focusing on these key bands also enhances the accuracy of classification algorithms, as redundant or irrelevant bands, which can introduce noise and lower model performance, are excluded. In this paper, we propose an approach for HS image classification using… 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 >