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A calibration scheme for SAR ADCs based on capacitor weight optimization using an improved simulated annealing algorithm

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MICROELECTRONICS JOURNAL 2025年 157卷

作者： Wang, Zhuofan Lang, Lili Zhong, Wei Shan, Yi Xue, Zhongying Dong, Yemin Chinese Acad Sci Shanghai Inst Microsyst & Informat Technol State Key Lab Mat Integrated Circuits Shanghai 200050 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Univ Chinese Acad Sci Ctr Mat Sci & Optoelect Engn Beijing 100049 Peoples R China

This paper proposes a foreground calibration method, which applies simulated annealing (SA) algorithm to the calibration of successive approximation register analog-to-digital converters (SAR ADCs). The capacitor weights are updated according to the performance metrics of the output codes, without necessitating any signal injection or modifying the analog structure of the SAR ADC. The methods of iterative and parallel solving, as well as variable searching step size are introduced into the SA calibration for adequate search. In addition, a multi- objective optimization strategy based on lexicographic optimization is used to take into account the performance of both signal-to-noise and distortion ratio (SNDR) and spurious-free dynamic range (SFDR). The estimated capacitor weights are applied in the digital domain to calibrate the SAR ADC output codes. The effectiveness of this calibration method is verified by simulating a 12-bit SAR ADC model with 2-bit redundancy and calibrating a 16-bit, 500 kS/s SAR ADC with 4-bit redundancy fabricated in 180 nm technology. The simulation results show the significant improvements in both SNDR and SFDR, along with a notable enhancement in integral nonlinearity (INL). 512 sinusoidal signal samples are collected on testing platform to extract the capacitor weights that can further contribute to the calculation of the output codes. The experiment results show that the SNDR and SFDR are improved by 20.04 dB and 20.19 dB, respectively, while the INL are enhanced by nearly 16 LSB.

关键词： Successive approximation register Analog-to-digital converter Capacitor mismatch simulated annealing algorithm Foreground calibration Optimization

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A fuzzy decision-making network model for offshore wind turbine selection based on simulated annealing algorithm

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OCEAN ENGINEERING 2025年 315卷

作者： Xue, Jie Yang, Hao Song, Yuanming Zhang, Chengwei Hu, Hao Shanghai Jiao Tong Univ Sch Ocean & Civil Engn 800 Dongchuan Rd Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ State Key Lab Ocean Engn Shanghai 200240 Peoples R China

As global demand for renewable energy surges, offshore wind power has become an indispensable component in the transition towards a more sustainable energy landscape. Selecting appropriate wind turbines for offshore wind power facilities is a critical process influenced by various factors, including turbine parameters, environmental conditions, and economic indicators. Traditional decision-making methods often fall short in addressing the complexity and dynamic nature of real-world scenarios, relying heavily on expert experience. This study proposes a novel and scalable method for offshore wind turbine selection by leveraging a fuzzy decision-making network and a conditional probability table optimized through a simulated annealing algorithm. The method is structured into three key modules. It allows for learning from existing similar cases and transferring knowledge to the current selection task in the absence of expert opinion. It has proven its worth in a case study at the Rudong Wind Farm in Jiangsu Province, China. The results show that this method can account for the complexities inherent in turbine selection and serve as a more comprehensive and adaptable tool for decision-makers. This study contributes to the renewable energy sector by providing a novel, data-driven, and practical method for offshore wind turbine selection and other real-world related applications.

关键词： Offshore wind power Wind turbine selection simulated annealing algorithm Multi-attribute decision-making Fuzzy decision-making network

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Design and simulation of thermal radiation image recognition based on simulated annealing algorithm in image VR creation and acquisition system

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THERMAL SCIENCE AND ENGINEERING PROGRESS 2025年 58卷

作者： Pan, Zhenzhen Wang, Feng Luan, Dongming Pan, Hong Chizhou Univ Sch Arts & Educ Chizhou 247000 Anhui Peoples R China Baekseok Univ Grad Sch Christianity Seoul 06695 South Korea Weifang Univ Sch Comp Engn Weifang 261061 Peoples R China Jilin Univ Dept Comp Sci & Technol Changchun 130012 Peoples R China Anhui Polytech Univ Sch Design Wuhu 241000 Anhui Peoples R China

With the rapid development of virtual reality (VR) technology, image acquisition system is becoming more and more important in VR content creation. Thermal radiation image recognition has great potential in improving the accuracy and quality of VR image acquisition. This paper aims to explore the thermal radiation image recognition method based on simulated annealing algorithm, and apply it to the design and simulation of VR creation acquisition system. In this paper, a thermal radiation image recognition method based on simulated annealing algorithm is proposed. The simulated annealing algorithm is used to optimize the feature extraction and matching process of thermal radiation images, which effectively solves the problem that the traditional method is easy to fall into the local optimal solution when processing complex images. Finally, a VR image acquisition system with integrated thermal radiation image recognition function is constructed, and several simulation experiments are carried out to verify its performance. The experimental results show that the thermal radiation image recognition method based on simulated annealing algorithm is superior to the traditional method in both accuracy and stability. The method can accurately identify the target region and effectively reduce the noise interference when processing the thermal radiation image in different scenes. The VR image acquisition system integrated with this recognition method performs well in practical applications, and significantly improves the quality and efficiency of image acquisition.

关键词： simulated annealing algorithm Thermal radiation image recognition Image processing VR creation acquisition system System design

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Experimental study of optimized graphene sheet layout with simulated annealing algorithm on cooling effect of the photovoltaic wall

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APPLIED THERMAL ENGINEERING 2025年 266卷

作者： Jin, Xiaoyu Zhou, Yan Zhang, Zhiwei Chen, Jinjin Ningbo Univ Sch Civil & Environm Engn & Geog Sci Ningbo 315211 Zhejiang Peoples R China Ningbo Key Lab Energy Geostruct Ningbo 315211 Peoples R China

Since the common cooling methods for the PV wall system are difficult to achieve better heat dissipation effect, this paper proposes a method for optimizing the layout of graphene sheet on the back of PV panel using the simulated annealing algorithm and 2-D finite difference method to improve cooling effect. The proposed method is used to compare different graphene sheet coverage rates and different grid sizes, taking minimum average temperature of the PV panel as optimization objective. The optimal layout with grid size of 100 mm x 100 mm and coverage rate of 60 % is chosen for experiment. The experimental results of comparison with the reference PV wall indicate that under natural convection, the average temperature reduction (Delta T-p) and output power increase rate (Delta E/E-r) of the PV-GS panel during 12:30 similar to 17:30p.m. in the 3 test days are 2.98 degrees C and 1.57%, respectively. And the average temperature reduction of the exterior surface (Delta T-we) is 2.38 degrees C. Under forced convection, the optimized graphene sheet layout has better cooling effect than natural convection. But the effects are unobvious when wind speeds increase from 1 m/s to 1.5 m/s and 2 m/s. Moreover, environmental and economic analyses of the PV-GS wall are also performed. Under natural convection, per square PV-GS wall can reduce CO2 emissions by 2.46 tons in the lifespan, and the payback period is only 3.18 years. The proposed method can not only be used in PV wall systems, but also can be applied to other BIPV systems and fields for enhancing heat dissipation.

关键词： Photovoltaic wall Graphene sheet layout Cooling effect simulated annealing algorithm Finite difference method

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Application of mixed integer programming and simulated annealing algorithm in sustainable logistics network design

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年

作者： Wang, Nana Liaoning Univ Int Business & Econ Sch Liberal Educ 33 Shunle St Dalian City 116052 Liaoning Provin Peoples R China

This article integrates mixed integer programming and the simulated annealing algorithm to enhance both the economic efficiency and environmental sustainability of logistics networks. A multi-objective optimization model is first developed, incorporating economic costs, carbon emissions, and social service levels to address the diverse needs of stakeholders. A solution approach combining the precision of mixed integer programming with the global search capabilities of the simulated annealing algorithm is then proposed. This hybrid approach effectively overcomes the limitations of traditional optimization methods, particularly in managing complex constraints and large-scale problems. Through practical case studies, the proposed method demonstrated superior optimization performance. The average total cost after optimization was $52,444.61, outperforming solutions derived from using either mixed integer programming or simulated annealing alone. Furthermore, the service satisfaction rate exceeded 90%, indicating the model's effectiveness in balancing multiple objectives. The findings of this study not only offer a novel theoretical framework for logistics network design but also provide valuable support for enterprises striving to achieve sustainable development in their operations. The research highlights the potential to strike a harmonious balance between economic, environmental, and social responsibilities, paving the way for more sustainable and efficient logistics practices.

关键词： sustainable logistics network design mixed integer programming simulated annealing algorithm multi-objective optimization model environmental friendliness

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Using simulated annealing algorithm to optimize three-dimensional spatial structure in environmental art design

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年

作者： Mao, Yilin Chengdu Coll Arts & Sci Dept Art 278 Xuefu Ave Chengdu 610000 Sichuan Peoples R China

Existing methods for optimizing three-dimensional spatial structures in environmental art design often rely on subjective experience and intuition, lacking scientific rigor and systematic quantitative analysis. This limitation frequently results in suboptimal solutions, particularly in multi-objective optimization scenarios where local optima are prevalent, thereby restricting innovation and practicality. To address these challenges, this paper proposes the use of the simulated annealing (SA) algorithm to optimize spatial structures. A multi-objective optimization model is constructed, integrating functionality, aesthetics, and space utilization, with mathematical modeling employed to quantify these objectives. To enhance solution quality, a hybrid strategy combining domain knowledge with Latin hypercube sampling ensures uniformity and representativeness of initial solutions. The SA algorithm is configured with carefully selected parameters, including initial temperature and cooling rate, while a comprehensive penalty function handles multi-dimensional constraints. The transition probability mechanism further improves global search capability, preventing premature convergence. Experimental results demonstrate the algorithm's superior performance: an average generation speed of 3.28 seconds/scheme, optimization time of 21.85 minutes, functional realization rate of 90.83%, space utilization rate of 94.79%, and significantly higher aesthetic scores compared to other methods. This study bridges the gap between artistic creativity and computational optimization, offering a transformative approach to spatial design. By enabling innovative, efficient, and balanced solutions, it advances intelligent methodologies in environmental art design, fostering sustainable and aesthetically pleasing environments.

关键词： environmental art design simulated annealing algorithm three-dimensional spatial structure design efficiency multi-objective optimization

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A weather station selection method based on the simulated annealing algorithm for electric load forecasting

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Neural Computing and Applications 2025年 1-20页

作者： Salmabadi, Narjes Salari, Majid Shadman, Alireza Department of Industrial Engineering Ferdowsi University P.O. Box 91779-4895 Mashhad Iran

Temperature is a key factor in modeling electricity demand, making the selection of optimal weather stations essential for accurate predictions. However, current methods for selecting weather stations often rely on heuristic approaches that explore only a limited subset of potential combinations, potentially missing better solutions. In this paper, we propose an innovative approach that integrates the simulated annealing (SA) algorithm with local search techniques to improve forecast accuracy and reduce implementation time. Our method demonstrates superior performance in both quality and efficiency compared to existing approaches, as validated across three datasets, including data from a major distribution company in Iran and the Global Energy Forecasting Competitions of 2012 and 2014. Our results show that incorporating local search techniques reduces the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) by 3.48% and 2.82%, respectively. Furthermore, the average implementation time of our SA algorithm is 36.52% lower than that of the existing metaheuristic algorithm. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Electric load forecasting Evolutionary computing simulated annealing algorithm Weather station selection

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Optimization of efficiency maximization strategy of automobile transmission system based on simulated annealing algorithm

ENGINEERING RESEARCH EXPRESS

引用

ENGINEERING RESEARCH EXPRESS 2025年第1期7卷

作者： Liu, Jincui Xinxiang Vocat & Tech Coll Xinxiang 453000 Peoples R China

Under the dual pressures of the global energy crisis and environmental protection, improving the efficiency of automotive transmission systems has become one of the core issues in the industry. This paper focuses on automobile transmission systems, proposes an innovative optimization scheme, and applies an SAA algorithm to solve the efficiency maximization problem. SAA is derived from the annealing principle in the physical field, which can effectively avoid local optimal traps and realize global search. It is especially suitable for dealing with complex multivariable optimization tasks. Firstly, a detailed mathematical model of the variable speed transmission system is established, covering key links such as gear meshing and friction loss, ensuring the accuracy of the analysis. Subsequently, many accurate vehicle test data were introduced, covering various driving conditions, such as urban roads and expressways, to verify algorithm effectiveness. Experiment mental data show that under normal working conditions, the average efficiency of the optimized transmission system is improved by about 5%. In contrast, under extreme conditions, such as high load and low speed, the efficiency is improved by more than 8%. The power ride comfort is unaffected, indicating the solution has high performance and practicality. In addition, through sensitivity analysis, it is found that several key parameters, such as drive shaft diameter and lubrication conditions, significantly impact the system efficiency, providing a direction for further refined adjustment.

关键词： simulated annealing algorithm automotive transmission system efficiency performance optimization

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A chaotic simulated annealing genetic algorithm with asymmetric time for offshore wind farm inspection path planning

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INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 2025年第2期25卷 69-78页

作者： Kou, Lei Wang, Yukuan Zhang, Fangfang Yuan, Quande Wang, Zhen Wen, Jingya Ke, Wende Qilu Univ Technol Inst Oceanog Instrumentat Shandong Acad Sci Qingdao Peoples R China Changchun Inst Technol Sch Comp Technol & Engn Changchun Peoples R China Southern Univ Sci & Technol Dept Mech & Energy Engn Shenzhen Peoples R China

The harsh environment of offshore wind farms causes wind turbines to be easily broken down. To ensure the normal operation of wind turbines, it is necessary to carry out inspections of offshore wind farms. Path planning is an important step to complete the inspection. The unmanned surface vessel (USV) is subject to the water current, leading to deceleration and acceleration, which makes the round-trip travelling time of the USV between two wind turbines asymmetric. To sum up, it belongs to asymmetric travelling salesman problem. To address this problem, a chaotic simulated annealing genetic algorithm (CSAGA) considering asymmetric time is proposed in this paper. Firstly, the initial sequence with high quality, as the initial solution of the simulated annealing algorithm, is generated by logistic-tent chaotic mapping. Then, effective solutions are obtained by a series of operations of the simulating annealing algorithm and is used to replace the worst fitness individuals in the initial population of the genetic algorithm. Finally, genetic operations such as selection, crossover, mutation, and reversion are applied to the population to obtain the optimal solution. The feasibility of the algorithm is verified by simulation experiments. The results display that CSAGA has better performances compared to other algorithms.

关键词： travelling salesman problem TSP inspection path planning simulated annealing algorithm genetic algorithm offshore wind farm

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simulated annealing algorithm for detecting graph isomorphism

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Journal of Systems Engineering and Electronics 2008年第5期19卷 1047-1052页

作者： Geng Xiutang Zhang Kai Dept. of Control Science and Engineering Huazhong Univ. of Science and Technology Wuhan 430074 P. R. China

Evolutionary computation techniques have mostly been used to solve various optimization problems, and it is well known that graph isomorphism problem （GIP） is a nondeterministic polynomial problem. A simulated annealing （SA） algorithm for detecting graph isomorphism is proposed, and the proposed SA algorithm is well suited to deal with random graphs with large size. To verify the validity of the proposed SA algorithm, simulations are performed on three pairs of small graphs and four pairs of large random graphs with edge densities 0.5, 0.1, and 0.01, respectively. The simulation results show that the proposed SA algorithm can detect graph isomorphism with a high probability.

关键词： graph isomorphism problem simulated annealing algorithm nondeterministic polynomial problem,local search.

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